Patent Publication Number: US-11025800-B2

Title: Systems and methods for imaging fine art paintings

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application claims the benefit under 35 U.S.C. § 119 of U.S. application No. 62/657,501 filed 13 Apr. 2018 and entitled APPARATUS AND METHOD FOR COLOR PHOTOGRAPHY OF GLOSSY FINE ART OBJECTS which is hereby incorporated herein by reference for all purposes. 
    
    
     FIELD 
     This invention relates to high precision imaging suitable for example for imaging fine art paintings. Example embodiments provide systems and methods that can be applied for determining color values of fine art paintings. The invention has example application in creating high quality digital representations of paintings. 
     BACKGROUND 
     Masterpiece paintings such as Leonardo da Vinci&#39;s “Mona Lisa” or Claude Monet&#39;s “Water Lilies” are admired across the world. Collectors, art enthusiasts, curators, tourists, etc. regularly attend public or private showcases of fine art paintings. However, placing a fine art painting on display exposes the painting to risks. The painting may, for example, be damaged by observers (e.g. oily hands), moisture, fire, exposure to light (e.g. damage from UV light, damage from exposure to camera flashes, etc.), etc. Displaying a fine art painting also may expose the painting to an increased risk of theft. Costly systems may be put into place to attempt to protect the painting from damage and/or theft (e.g. anti-theft measures, fire prevention systems, environmental control systems, etc.). 
     Recent developments in three-dimensional color printing make it feasible to produce high quality reproductions of fine art paintings. Having a faithful reproduction of a painting would allow for a replaceable reproduction to be displayed while an original is stored in a secure location. In addition, high quality reproductions may permit enjoyment of a painting by people who cannot access the original. 
     Faithfully reproducing a painting requires producing a copy as close as possible to the original painting. This, for example, requires reproducing the visual appearance of the original painting when the reproduction is illuminated using similar lighting conditions, viewed from similar positions, etc. One important aspect for achieving this goal is accurately reproducing color values present in the original painting. 
     Gloss (e.g. “shininess”) can have a significant impact on how color values are perceived. It is common for artists to use glossy paints in their artwork. Glossy paintings tend to have colors that are more saturated than colors of matte paintings. Additionally, or alternatively, many artists finish their work by varnishing or coating their work with a glossy finish. 
     One way to determine colors that are present in a painting is to capture images of the painting and to process these images to determine color values. Typically, one or more light sources illuminate the painting while an image of the painting is captured. However, given the inherent glossy nature of many paintings, specular highlights often result during this process. Specular highlights occur at positions on a painting where the geometry of the painting&#39;s surface combines with an incident angle of light illuminating the painting in such a way that the incident light is reflected towards an observer (e.g. a person&#39;s eye or a lens of a camera being used to capture images of the painting). 
     Obtaining an accurate representation of color values present within a painting is complicated by the presence of specular highlights. Specular highlights typically result in a perceived (or captured) color that is lighter than the correct body color. Depending on how much light is reflected towards the imaging detector and the true color of the painting at that position, specular highlights may result in a color that is significantly lighter than the correct color. For example, a color at a position of the painting that is black may be perceived as being white in some cases when a specular highlight is present at the location. In many cases, a perceived lightness of a color value exceeds what would be perceptible of any matte object. 
     Many paintings are not completely flat (planar). Various painting techniques can produce surfaces that have significant variations in elevation (e.g. variations on the order of millimeters) as a result of brush strokes, applications of thick layers of paint, applications of multiple layers of paint, etc. These contours can further complicate obtaining correct color values for locations on a painting. 
     Laser scanners can be used to obtain both colorimetric information and 3D position information about points on a surface. Such scanners use light from plural laser light sources that emit light at different wavelengths. A problem with relying upon such laser scanners for making accurate color measurements is that the scanners are not sensitive at wavelengths other than the laser wavelengths. Since the human eye is sensitive to light having a broad range of wavelengths, two points which a laser scanner indicates to have the same color may not appear to be the same color to a human observer. 
     There is a general desire for practical systems and methods that can be applied to accurately determine color values that are present at positions within a painting or similar object. There is also a general desire for systems and methods for producing high quality digital and/or physical reproductions of fine art paintings. 
     SUMMARY 
     Further aspects and example embodiments are illustrated in the accompanying drawings and/or described in the following description. 
     One aspect of the invention provides a method for generating color map images of paintings. The color map image may represent color values of a painting as a function of position in the painting. The method may comprise, for each of a plurality of overlapping regions of the painting, acquiring a set of images. The set of images may comprise a plurality of images with different ones of the plurality of images acquired while the region is illuminated by light incident on the region of the painting from different directions. The imaging may be performed by an imaging device including an imaging sensor and an optical system arranged to focus an image of the region of the painting onto the imaging sensor. The optical system may have an object space telecentric configuration wherein chief light rays from points in the region that are parallel to an optical axis of the optical system pass centrally through an aperture of the optical system. A front element of the optical system closest to the painting may be at least as large as the region. The method may also comprise processing each of the plurality of sets of images to provide a processed image of the corresponding region of the painting from which one or both of specular highlights and shadows are removed or reduced. The method may also comprise registering the overlapping processed images together to generate the color map image. 
     In some embodiments processing each of the plurality of sets of images to remove or reduce one or both of specular highlights and shadows comprises comparing lightness values for corresponding pixels of different images in the set of images being processed to identify pixels in each of the images for which lightness values differ by more than a threshold amount from lightness values for the corresponding pixels in other ones of the images. 
     In some embodiments the method comprises analyzing surface geometry of the painting in a patch surface surrounding a pixel and based on the geometry determining whether one or more corresponding values of the pixel represent a specular highlight or shadow. 
     In some embodiments generating the processed image for a region comprises combining corresponding pixel values of the plurality of images while excluding from the combining any pixel values identified as corresponding to a specular highlight or shadow for each pixel in the set of images of the region. 
     In some embodiments combining the corresponding pixel values comprises determining a single representative value for the corresponding pixel values from the plurality of images. 
     In some embodiments determining the single representative value comprises one or more of determining an average value, determining a median value and determining a mode value for the corresponding pixel values from the plurality of images. 
     In some embodiments the method comprises conditioning the images of the set of images. The conditioning may comprise one or more of reducing radial distortion of pixels, compensating for non-perpendicularity of the central optical axis relative to the painting, compensating for non-uniform detection of lighting values and correcting color values. 
     In some embodiments the method comprises translating the optical system and imaging sensor relative to the painting to image the different overlapping regions of the painting. 
     In some embodiments the method comprises, for each of the plurality of images, controlling a light source to emit light that is incident on the region at an angle to a plane of the painting and from a different direction. 
     In some embodiments the light source emits collimated light and an angle of incidence of the light beam onto the region is the same across a field of view of the optical system. 
     In some embodiments the light source comprises a set of light sources arranged in a line. 
     In some embodiments the emitted light has uniform intensity across a field of view of the optical system. 
     In some embodiments, for a plurality of points on a surface of the painting and radially spaced apart from the central optical axis, the points have differing elevations and the optical system eliminates or reduces radial shifting of colors at the imaging sensor. 
     In some embodiments, for a plurality of points on a surface of the painting, the points having varying elevations, the optical system projects the plurality of points onto an imaging plane of the imaging sensor with a substantially constant magnification as a distance between the front element of the optical system and the painting is adjusted. 
     In some embodiments the optical system reduces or removes parallax error corresponding to acquiring images of a point on a surface of the painting in different overlapping regions. 
     In some embodiments the method comprises scanning the painting with a laser scanner to collect color data representative of the painting. The method may also comprise refining the laser color data with the generated color map image. The refining may comprise registering the laser color data with the generated color map image. The refining may also comprise populating a look-up table using color values from the generated color map image and color values from the laser color data, the look-up table corresponding to a color gamut of pigments used to create the painting. The method may also comprise replacing one or more color values from the laser color data that do not match color values from the look-up table with color values from the look-up table. 
     In some embodiments the method comprises processing the laser color data prior to refining the laser color data, the processing comprising one or more of scaling the laser color data, reducing shading effects present in the laser color data and reducing specular highlights present in the laser color data. 
     In some embodiments the method comprises masking out values of pixels in the generated color map image prior to populating the look-up table, the masked out values representing one or more of photometric shading, cast shadows and specular highlights. 
     In some embodiments the laser scanning comprises scanning the painting at first and second complementary angles. 
     In some embodiments the laser scanner comprises a 450 nm, a 532 nm and a 638 nm single-mode laser. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Exemplary embodiments are illustrated in referenced figures of the drawings. It is intended that the embodiments and figures disclosed herein are to be considered illustrative rather than restrictive. 
         FIG. 1  is a schematic illustration of an example system for scanning a fine art painting. 
         FIG. 2  is a schematic illustration of an example imaging system that may be used by the  FIG. 1  system. 
         FIGS. 2A and 2B  are schematic illustrations of example arrangements of light sources. 
         FIG. 3A  is a schematic illustration showing an example focal plane of a conventional fixed focal point lens. 
         FIG. 3B  is a schematic illustration of an optical system according to an example embodiment. 
         FIG. 3C  is a schematic illustration of an optical system according to an example embodiment. 
         FIG. 4  is a schematic illustration showing an example optical system relative to a painting. 
         FIG. 5  is a schematic illustration showing an example light source. 
         FIGS. 6A and 6B  are schematic illustrations showing example systems for collimating light. 
         FIG. 7  is a schematic illustration showing an example intensity function of a light source. 
         FIG. 8  is a schematic illustration showing an example arrangement for collimating light. 
         FIGS. 9-11  are flow charts showing methods according to example embodiments. 
         FIG. 11A  is a schematic illustration showing an example color calibration target. 
         FIG. 12  is a flow chart showing a method according to an example embodiment. 
         FIGS. 13A-13C  are schematic illustrations showing an example image registration. 
         FIG. 14  is a flow chart showing a method according to an example embodiment. 
     
    
    
     DETAILED DESCRIPTION 
     Throughout the following description, specific details are set forth in order to provide a more thorough understanding of the invention. However, the invention may be practiced without these particulars. In other instances, well known elements have not been shown or described in detail to avoid unnecessarily obscuring the invention. Accordingly, the specification and drawings are to be regarded in an illustrative, rather than a restrictive sense. 
     Three-dimensional (3D) printers may be used to reproduce fine art paintings. The reproductions can capture both the three-dimensional shape of the paintings and the distributions of colors and tone in the paintings. For example, a 3D printer may be used to produce reproductions of works by artists such as Vincent van Gogh, Claude Monet, Pablo Picasso, etc. 3D printers are commercially available. For example, 3D printers manufactured by Océ Technologies B.V. of Venlo, Netherlands may be used to print reproductions of paintings. 
     However, creating a high quality reproduction of a painting requires sufficiently detailed and accurate information about the original painting. With good enough information about the original painting it is possible to make a reproduction that is virtually indistinguishable from an original painting. “Virtually indistinguishable” means that an untrained eye is unable to distinguish an original painting from a reproduction from a distance of 1.5 meters. In some embodiments the systems and methods described herein are used to create reproductions that are virtually indistinguishable from the originals. 
     One aspect of creating a high quality reproduction is to print at a high enough resolution. In some embodiments features present in a painting are reproduced (e.g. “printed”) using a resolution that is the same as, or better than, the maximum resolution perceptible by a human eye. In some embodiments a 3D printer is controlled to print with a lateral resolution of 50 to 100 microns or less. For example, the pitch distance between centers of adjacent pixels may be about 0.12 mm or less. To achieve this one should have data describing the painting that has a resolution equal to or higher than the printing resolution. 
     Reproducing features present in a painting may comprise printing a plurality of layers of UV-curable polymer on top of one another. This may, for example, be used to reproduce brush strokes that are present in a painting. Additionally, or in the alternative, features present in a painting may be reproduced using thermoforming. Thermoforming may comprise printing a colored layer onto a thin thermoplastic sheet. The thermoplastic sheet may then be thermoformed to a physical mold that is dimensioned to produce a desired surface elevation profile. 
     To reproduce a painting one must have data that accurately describes the painting at a sufficiently high resolution. Such data may be communicated to a 3D printer or other reproduction device. Such data may, for example, include:
         an elevation map that describes the height at any position within the painting as a function of the position; and   a color map that specifies color values for each location within the painting.       

     In preferred embodiments, the elevation map and the color map image (each a “data image”) represent the same physical space and have the same pixel size and shape, orientation and pixel origin. For example, such a map may specify for each pixel in an x-y plane an elevation corresponding to the pixel and a set of values which represent the color of the pixel in a suitable color space. However this is not mandatory. In some embodiments, a mathematical transformation (or multiple mathematical transformations) may be applied to scale attributes (e.g. physical space, pixel size and/or shape, orientation, pixel origin, etc.) of one data image to match attributes of another data image. 
     In some embodiments the elevation map comprises a two-dimensional (2D) image comprising pixels each associated with a greyscale (scalar) value encoding height. Each greyscale height value may represent a height (or elevation) of the painting relative to a reference plane or other surface at a location represented by the pixel. In some embodiments, the elevation image may be associated with a scaling factor or scaling function that allows greyscale intensity values of the pixels to be converted into elevation values measured using units of length. 
     In some embodiments, each pixel is square. This is convenient but not mandatory. 
     The color map image may encode surface color values of the painting by way of values in a suitable color space. In some embodiments, a color space that is used to encode color values in the color map image may directly correlate to a color space of the 3D printer to be used in printing a reproduction (e.g. the color space may specify color in terms of the same primary colors provided by the printer). The color space should encompass a gamut large enough to record the colors used in a painting. In some embodiments the Adobe™ 1998 color space is used. Other example color spaces that may be used include:
         sRGB;   ProPhoto™ RGB;   scRGB;   CIE RGB   LUV   YUV   CIELAB.       

     One aspect of the invention provides improved systems useful for generating color map images of fine art paintings. Such systems may reduce or eliminate the effect of specular highlights and may generate color map images of sufficient quality to produce high quality reproductions (or, in some cases virtually indistinguishable reproductions) of the fine art painting. In some embodiments color data from a color map image generated by capturing images of painting  2  (e.g. photographing painting  2 ) is processed to correct and/or improve color data collected by laser scanning painting  2 . 
       FIG. 1  schematically shows an example system  20  which may be applied for generating one or more color map images of a painting  2 . 
     System  20  comprises an easel  22  and an imaging system  23  that is movable relative to easel  22  by a scanning system  29 . Scanning system  29  is controllable to position imaging system  23  in selected positions relative to a painting supported on easel  22 . Scanning system  29  may comprise any suitably precise positioner. For example, scanning system  29  may comprise an X-Y positioner that can controllably move imaging system  23  along each of two orthogonal axes. 
     Scanning system  29  preferably moves imaging system  23  in a plane that is parallel to a plane on which easel  22  holds a painting  2  to be imaged. In the illustrated embodiment, imaging system  23  is carried by a mount  24  which is movable in a first (e.g. horizontal) direction (e.g. left to right and vice versa as shown in  FIG. 1 ) by actuator  25  and is movable in a second (e.g. vertical) direction (e.g. into and out of the page as shown in  FIG. 1 ) by actuator  26 . The axes of motion provided by actuators  25  and  26  may be orthogonal to one another. Scanning system  29  optionally includes an actuator that can move mount  24  to adjust a distance of imaging system  23  relative to painting  2 . Such an actuator may be operated to compensate for curvature in painting  2  and/or tilt of painting  2  relative to the plane defined by orthogonal axes of scanning system  29 . Scanning system  29  may optionally achieve relative motion of imaging system  23  and easel  22  on one or more axes by moving easel  22  instead of or in addition to moving imaging system  23 . 
     Scanning system  29  may have any of a wide variety of configurations. Suitable high precision positioning systems are commercially available from a wide range of suppliers. 
     In preferred embodiments actuators  25  and/or  26  smoothly translate imaging system  23 . Smoothly translating imaging system  23  may preserve alignment of imaging system  23  relative to painting  2 . 
     Two or more of mount  24 , actuator  25  and actuator  26  may be combined into a single actuator. In some embodiments, scanning system  29  comprises a single actuator having at least three degrees of freedom to translate imaging system  23  relative to painting  2 . 
     In some embodiments scanning system  29  (e.g. one or more of mount  24 , actuator  25  and actuator  26 ) may vary both a position of imaging system  23  and an orientation (e.g. roll, pitch, yaw) of imaging system  23  relative to painting  2 . In some embodiments, scanning system  29  is associated with a positioning error map that characterizes deviations between actual and ideal position and/or orientation of imaging system  23  when scanning system  29  is set to a specific position. The positioning error map may be used to correct the position and/or orientation of imaging system  23  and/or to correct a correlation between pixels in images acquired by imaging system  23  and points on a painting  2 . 
     In some embodiments scanning system  29  (alone or in combination with imaging system  23 ) focuses imaging system  23  on a surface of painting  2 . In some embodiments imaging system  23  is operative to automatically focus on a surface of painting  2 . Additionally, or alternatively, a position and/or orientation of imaging system  23  relative to painting  2  and/or a lens of imaging system  23  may be manually adjusted to focus imaging system  23  on a surface of painting  2 . Since the surface of painting  2  is generally not flat, imaging system  23  may be focused on a plane that is intermediate between high and low points on the surface of the painting. Imaging system  23  may have a depth of field sufficient to capture sharp images of the surface of the painting. 
     System  20  comprises light sources  32  (described below) that may be operated to illuminate painting  2 . Light sources  32  are configured to facilitate illuminating painting  2  under different illumination conditions. The illumination conditions may differ, for example, by the direction from which light is incident on painting  2 . 
     System  20  may include an enclosure  27  which encloses easel  22 , imaging system  23  and scanning system  29 . Enclosure  27  may block ambient light from illuminating painting  2  and/or protect painting  2  from damage. Enclosure  27  may shield painting  2  and/or imaging system  23  from environmental influences such as wind, air drafts, dust, etc. Enclosure  27  may further protect painting  2  from influences that could alter positioning of painting  2  relative to imaging system  23 . Painting  2  may be positioned within an internal cavity  21  of enclosure  27 . Enclosure  27  may be removable, include an opening, include a door, and/or the like to facilitate insertion and/or removal of painting  2  into internal cavity  21 . 
     In some embodiments, system  20  comprises feet that reduce, or eliminate movement of system  20  as a result of environmental disturbances (e.g. floor vibrations, a person bumping into system  20 , wind drafts, etc.). One or more surfaces of the feet may be coated with a vibration damping material. Additionally, or alternatively one or more shock absorbing couplings may be incorporated into the structure of system  20 . 
     Easel  22  may hold painting  2  within cavity  21  of system  20 . In some embodiments easel  22  comprises a lower ledge on which a surface of painting  2  may be rested. In some embodiments one or more surfaces of easel  22  frictionally engage opposing surfaces of painting  2 . In some embodiments one or more surfaces of easel  22  are coated with a vibration dampening material. Easel  22  may be configured to reduce motion of painting  2  that may distort captured images of painting  2  (e.g. vibrations of painting  2 , displacement of painting  2  relative to easel  22 , etc.). In some embodiments easel  22  is rigidly mounted within cavity  21 . In some embodiments easel  22  is integral with enclosure  27 . 
     In some embodiments system  20  comprises a scanner  28  which may be operated to map surface elevations and/or color values of painting  2  as a function of position within painting  2 . In some embodiments scanner  28  is a laser scanner. For example, scanner  28  may comprise an RGB scanner. The RGB scanner may emit light at a plurality of wavelengths. In some embodiments scanner  28  comprises a plurality of single-mode lasers. For example, scanner  28  may comprise single-mode lasers that emit light having wavelengths of 450, 532 and 638 nm. Scanner  28  may be mounted to be moved by scanning system  29 . For example, scanner  28  may be coupled to mount  24 . In some such embodiments data acquired by scanner  28  (elevation values and/or color values) and data acquired by imaging system  23  (color values) may be acquired in the same image space and may be correlated to one another relatively easily (i.e. by identifying the elevation value and color value(s) corresponding to a particular position within painting  2 ). 
     A scanning mirror may focus and/or project light (e.g. laser beams) from scanner  28  onto a surface of painting  2 . A light detector of scanner  28  may collect light that is scattered from a point on painting  2 . Scanning system  29  may be operated to move scanner  28  through a range of positions so that scanner  28  acquires data for the full area of painting  2 . 
     In some embodiments scanner  28  and imaging system  23  are coupled to scanning system  29  together (e.g. adjacent one another on mount  24 ). In some embodiments scanner  28  and imaging system  23  are coupled to scanning system  29  interchangeably. For example, scanner  28  may be coupled to mount  24  and operated to scan a painting  2  and then imaging system  23  may be coupled to mount  24  and used to scan painting  2  or vice versa. In such embodiments one of imaging system  23  and scanner  28  scans painting  2  at a time. 
     Scanner  28  may comprise a translation stage. The translation stage may be operated to adjust the angle of incidence of scanning light relative to a normal vector of painting  2  (i.e. a vector perpendicular to a plane of painting  2 ). In some embodiments scanner  28  scans painting  2  with light incident at two angles (e.g. +/−20 degrees). In some such embodiments scanner  28  scans to determine elevations or elevations and colors along each scan line of painting  2  twice. Each scan of the scan line may use light incident on painting  2  at a different angle of incidence. For example, the scan lines may be horizontal lines across painting  2 . A different horizontal line may be scanned by translating scanner  28  vertically. Scanner  28  may, for example, scan the horizontal line at a desired angle of incidence in one direction and may proceed to scan the horizontal line a second time at a complementary angle of incidence by rotating the scanner to the complementary angle and traversing the same horizontal line in reverse. 
     Imaging system  23  is operative to capture images of painting  2 . Typically, each image captured by imaging system  23  corresponds to a region of painting  2  that is smaller than the entire area of painting  2 . Scanning system  29  may be operated to position imaging system  23  for acquiring images of each region. In such typical cases obtaining a color map of painting  2  requires obtaining images of regions which collectively cover the whole area of painting  2 . Each of the regions preferably overlaps with some neighboring regions. 
     Scanning system  29  and/or easel  22  may be controlled to move imaging system  23  (and/or scanner  28 ) relative to painting  2  to the positions required to image all of the regions. Images of different regions of painting  2  may be registered together to generate a color map image of painting  2  as described herein. 
     System  20  may be operated to capture images of each region under each of a plurality of different lighting conditions. In some embodiments system  20  is controlled to capture sets of images of painting  2 . Each set of images may correspond to a different region of painting  2 . Each image in a set of images may be captured using a different lighting condition (e.g. using a different light source  32  or set of light sources  32 ). The lighting conditions may differ from one another in the direction from which the light is incident on the region of the painting  2  being imaged. The sets of images may be processed to generate a color map image  102  of painting  2 . 
     The imaged regions of painting  2  may be chosen such that adjacent regions overlap by at least an amount necessary to accurately stitch images of the adjacent regions together. In some embodiments two adjacent regions overlap by a distance equal to 50% of a width of each region. In some embodiments each region of painting  2  that is imaged overlaps with its adjacent regions by an equal amount. In some embodiments each region overlaps with at least one neighboring region by a distance that is at least 100 times greater than a pitch of pixels in the image. For example in the case where the image has a resolution of 200 pixels per 25 mm the neighboring regions may overlap by at least 12.5 mm. 
     In some embodiments a size of painting  2  may be ascertained by system  20 . For example, system  20  may move imaging device  23  across painting  2  while processing images captured by imaging device  23  and/or information (e.g. elevation and/or color information) from scanner  28  to detect corners or edges of painting  2 . In some embodiments a size of painting  2  is communicated to system  20  by a user. Data may be communicated to system  20  using any presently known or future discovered method of communicating data to a system. The size information may be used to establish the locations of overlapping regions to be imaged and corresponding locations at which imaging device  23  should be positioned to image each of those regions. If optional scanner  28  is included, the size information may be used to determine locations at which scanner  28  may be positioned to scan painting  2 . 
     In some cases painting  2  is decoratively framed. Removing a painting from a decorative frame may damage the painting. In some embodiments system  20  detects the presence of a decorative frame. In such embodiments system  20  may ignore the decorative frame when computing the size of painting  2  and/or capturing images of painting  2 . 
     Preferably an optical axis of imaging system  23  is oriented perpendicular to a plane of painting  2 . 
     A front element of a lens of imaging system  23  may be separated from painting  2  by a working distance w d . “Working distance w d ” is the distance between the end of an optical system of imaging system  23  (e.g. optical system  31  of  FIG. 2 ) that is closest to painting  2  and a surface of painting  2 . 
     w d  may be comparatively small. In a preferred embodiment w d  is about 150 millimeters. In some embodiments w d  is less than 1 meter. In some embodiments w d  is in the range of 100 millimeters and 300 millimeters. In some embodiments w d  is the same as a working distance of elevation scanning system  28  used to generate the corresponding elevation map. 
     Scanning system  29  may be configured so that working distance w a  is fixed. In some embodiments scanning system  29  is configured to permit control of working distance w a  (e.g. by controlling a position of imaging device  23  in a direction perpendicular to easel  22 ). As described elsewhere herein, mount  24  may be operable to adjust working distance w a . Some embodiments provide a manual adjustment that can be operated to adjust working distance w a . 
       FIG. 2  shows an example imaging system  23 . Imaging system  23  comprises a camera  30  having an imaging sensor. Camera  30  captures images of painting  2  (or any other objected positioned on easel  22 ). An optical system  31  collects light and focuses the light onto the imaging sensor of camera  30 . 
     Optical system  31  comprises a compound lens having elements arranged as an object space telecentric lens. Optical system  31  has an entrance pupil at infinity. In some embodiments optical system  31  has both an entrance pupil and an exit pupil at infinity (e.g. optical system  31  comprises a “bi-telecentric lens” or a “double telecentric” lens). Advantageously, embodiments where optical system  31  is a bi-telecentric lens may allow for additional control over directions from which rays are incident on an imaging device sensor (e.g. an imaging sensor of camera  30 ). 
     A front element of optical system  31  closest to painting  2  is at least as large as each region being imaged. 
     The design of optical system  31  as a telecentric lens avoids distortions that could occur with ordinary lenses and therefore facilitates more accurate stitching together of images for different regions into a color map. This also facilitates registering pixels of a color map with pixels acquired by a scanning device (e.g. a laser scanner as described elsewhere herein). Pixels of different sets of images that correspond to the same part of painting  2  (e.g. in areas of overlap between the regions of the different sets of images) should appear the same when imaged and should provide color values that come from the same locations on painting  2 . However, where the surface of paining  2  is textured (not flat) the varying elevations of painting  2  (e.g. typically 5-10 mm but may be 20 mm or more) can result in radial shifting of pixels when a conventional lens is used. Radial shifting of corresponding pixels may complicate registration of the sets of images, distort color map image  102  and/or the like. This effect, which is illustrated in  FIG. 3A  is exacerbated where working distance w a  is small (e.g. less than 1 m) as described elsewhere herein. 
       FIG. 3A  schematically illustrates that surface  36  of painting  2  can have varying elevations within a region being imaged. It is desired that each position on painting  2  corresponds to one corresponding point in image plane F Ip . This way the color values detected by an image sensor in image plane F Ip  can be associated to a specific corresponding location on painting  2 . 
       FIG. 3A  shows the case where painting  2  is imaged using a conventional lens. Point  37 A aligns with a longitudinal central optical axis of a conventional lens  35 . Point  37 , which is a projection of point  37 A onto a focal plane F p  of lens  35 , therefore aligns directly with point  37 A. However, for points on painting  2  located away from the central optical axis of lens  35 , differences in elevation at the points can cause the color recorded at a location on image plane F Ip  which should correspond to the color at a specific location on painting  2  to instead record the color at a radially shifted location. For example, points  38 ′ and  39 ′ in image plane F Ip  correspond to locations  38  and  39  in painting  2  and should record colors at the X-Y positions of locations  38  and  39  respectively. Due to the elevation changes in painting  2 , however, point  38 ′ records the color at point  38 A and point  39 ′ records the color at point  39 A. Point  38 A is radially shifted from point  38  by an amount r 1 . Point  39 A is radially shifted from point  39  by an amount r 2 . Thus, images of some locations of painting  2  are radially shifted in the image plane. 
       FIG. 3B  illustrates how optical system  31  avoids the radial shift described above. Since optical system  31  is configured to have an entrance pupil at infinity, surface  36  of painting  2  appears flat from the point of view of imaging device  23  irrespective of working distance w d . Furthermore, magnification does not vary with distance. This, for example, may be achieved by configuring optical system  31  to collect central rays (“chief rays” that pass through the centre of an aperture of optical system  31 ) from points on surface  36  parallel to central optical axis A 1  (see e.g.  FIG. 3B ). Advantageously, optical system  31  may reduce or eliminate parallax error and/or changes in magnification of points on surface  36  as a function of working distance w a . 
     As shown in  FIG. 3C , projections  37 ,  38  and  39  of points  37 A,  38 A and  39 A respectively onto focal plane F p  are not radially shifted by optical system  31  as a result of any changes in elevation of the surface of painting  2 . 
     However, using optical system  31  limits a size of a region of painting  2  that may be captured in a single image. A region of painting  2  to be imaged must fit within an area corresponding to a lens diameter of optical system  31 . For example, if painting  2  is a 1 meter high by 1 meter wide painting, capturing painting  2  in a single image would require an optical system  31  that has a diameter of at least about 1.41 meters (see e.g.  FIG. 4 ). This is usually impractical. Instead, system  20  captures sets of images of different regions of painting  2  that may be registered together (e.g. using the methods described elsewhere herein) to generate a color map image of painting  2 . 
     In preferred embodiments camera  30  stores captured images in an uncompressed format. For example, the uncompressed format may be a commercially known RAW format. Compressing captured images may distort elements of the captured images such as white balance, color values, etc. 
     In preferred embodiments imaging system  23  is aligned relative to painting  2  such that central optical axis A 1  is perpendicular to a plane of painting  2 . This alignment may be achieved, for example, with the aid of a flat mirror positioned on easel  22  or otherwise positioned to be parallel to a plane of painting  2 . The mirror may be marked with a target such as cross-hair (e.g. a “+” sign) printed or applied to a surface of the mirror. Alignment of imaging system  23  can be checked by taking an image of the target and mirror and verifying that a feature of imaging system  23  is in a desired location relative to the target. For example alignment may be confirmed when the captured images include an image of a circular lens of imaging system  23  being centered relative to an image of the target. 
     In some cases additional factors may need to be considered when aligning imaging system  23  with painting  2 . For example, when painting  2  is not flat there is some ambiguity in defining the plane of painting  2 . Painting  2  may, for example, have brushwork at varying elevations. In some cases, brushwork has elevations in a range of about 5-10 millimeters. In some cases, brushwork has an elevation up to 20 millimeters. In some cases brushwork has an elevation of more than 20 millimeters. 
     As another example, painting  2  may be non-planar. In some cases, a stretcher supporting a canvas of painting  2  may be warped thereby resulting in a painting  2  that is non-planar. As another example, painting  2  may comprise a work directly painted onto a non-planar substrate such as wood. Alignment of imaging system  23  may take into consideration the non-planar nature of painting  2  (if applicable). 
     In some embodiments, positions of imaging system  23  and/or painting  2  are dynamically varied to align optical system  31  with painting  2 . For example, mount  24  and/or easel  23  may dynamically align optical system  31  with a region being imaged. 
     In some embodiments a stabilizer such as a gimbal or similar device maintains imaging system  23  in a substantially constant alignment relative to painting  2 . Additionally, or alternatively, captured images may be processed and/or calibrated to correct misalignments of imaging system  23  relative to painting  2 . 
     As described elsewhere herein, light incident on painting  2  may result in specular highlights. Different incident angles may result in different pixels being affected by specular highlights. Additionally, or in the alternative, when light is incident on painting  2  projecting parts of painting  2  may cast shadows. Differing elevations of painting  2  may result in shadows being cast across lower elevation portions of painting  2  depending on incident angles of light. Shadows may result in colors appearing darker than their true value. Different incident angles may result in different pixels being affected by shadows. 
     For each region of painting  2  that is imaged, imaging system  23  may be controlled to capture a set of images using a different lighting condition. Each lighting condition may correspond to a different incident angle and/or direction of light. Since the locations of specular reflections and shadows can depend on the incident angle and/or direction of light, different pixels will be affected by shadows and/or specular reflections in different images of the set of images. Further, for any given pixel there is a likelihood that for at least some of the lighting conditions the pixel is neither affected by specular reflection or a shadow. A greater number of lighting conditions tends to reduce the likelihood that at least some of the lighting conditions will yield images which record the true color of each pixel in the images of the region of painting  2 . 
     System  20  may comprise a plurality of light sources  32 - 1 , . . . ,  32 -N (collectively or generally light source  32 ). Light sources  32  may be used to illuminate a region of painting  2  that is being imaged. Light sources  32  may be mounted peripherally around camera  30  and/or optical system  31  (see e.g.  FIG. 2 ). Each light source  32  may emit light that is incident on painting  2  at a different angle. 
     In some embodiments system  20  comprises two light sources  32  (N=2). In some embodiments system  20  comprises in the range of 2 to 8 light sources  32  (2&lt;N≤8). In some embodiments system  20  comprises more than 8 light sources (N&gt;8). Four light sources has been found to be sufficient. Light sources  32  may be generally linear (e.g. rows of light emitters). 
     Although light sources  32  are illustrated as being oriented symmetrically around optical system  31  in  FIG. 2 , this is not mandatory. Light sources  32  may be arranged around optical system  31  and/or camera  30  in any orientation. Symmetrically arranging light sources  32  may however reduce the likelihood of each light source  32  resulting in a specular highlight or cast shadow for a specific position within painting  2 . In preferred embodiments light sources  32  are arranged symmetrically around optical system  31  and/or camera  30 . For example, if imaging system  23  comprises 4 light sources, each of the light sources may be separated by 90 degrees from the other light sources (see e.g.  FIG. 2A ). 
     Light sources  32  may be oriented to emit light at any angle. In some embodiments light emitted from each of light sources  32  is incident with the plane of painting  2  at about a 45 degree angle. 
     In some embodiments system  20  comprises a single light source that may be moved to a plurality of positions around optical system  31  and/or camera  30 . For example, the light source may move to different positions around a track that extends around optical system  31  and/or camera  30  (see e.g.  FIG. 2B ). 
     Preferably each light source  32  emits a substantially identical light beam. Each light source may comprise a light bulb, LED source or the like. 
     A controller may control the overall operation of system  20  including operations such as:
         when camera  30  captures an image;   which of light sources  32  illuminates painting  2  when each image is being acquired;   where imaging device  23  is positioned for each image;   etc.       

     In some embodiments some images may be taken using light from two or more light sources  32 . 
     Preferably, a light beam corresponding to a lighting condition is incident at an identical angle across a field of view being imaged. In addition, a light beam corresponding to a lighting condition preferably has uniform intensity across the field of view. 
     In some embodiments, a light source generates a light beam that is extended in one direction relative to the field of view. For example, light source  32  may be extended in the horizontal or vertical direction. In preferred embodiments, light sources  32  are extended at least in one direction. Extending a light source may tend to equalize illumination intensity in a direction parallel to the extension. A light source may, for example, be extended by an amount that is double the greater of the width or the height of the field of view (the region of painting  2  being imaged). In some embodiments an extended light source comprises a plurality of light sources arranged in a line (see e.g.  FIG. 5 ) or a light guide that emits light along a line. 
     A light source may also be extended in a second direction so that the light is emitted over a wider area (e.g. a rectangular area). 
     Light sources may include lenses or other optical elements to improve illumination of a region being imaged. For example a lens  34  may be provided in a light path between a light source  32  and painting  2  as shown in  FIG. 6A . Illumination lens  34  may act to collimate the light incident on painting  2 . 
     Illumination lens  34  may, for example comprise a cylindrical telecentric lens. To illuminate all of a field of view having a maximum extent on the order of 60 mm, for example, the light source may emit a beam of light having a width of at least approximately 60/√{square root over (2)} mm (approximately 42 mm). Lens  34  may have a compound lens design as described, for example, in W. J. Smith in Modern Lens Design, Second Edition, McGraw Hill, New York, 2005. 
     In some embodiments lens  34  may collimate light in both horizontal and vertical directions across the field of view. In such embodiments light source  32  may comprise a point source (e.g. a single LED) or a plurality of point sources (e.g. a line of LEDs) in the direction which has not been collimated (see e.g.  FIG. 6B ). 
     In some embodiments light sources  32  are located relatively far from painting  2 . Positioning light source  32  far from the field of view may equalize path lengths from different parts of a light source  32  to various portions of the field of view such that the illumination is more uniform over the field of view. The distance between light sources  32  and painting  2  may be limited by the available space in some cases. 
     In some embodiments light source  32  comprises a light source in which the intensity of emitted light varies with angle.  FIG. 7  is a graph which shows schematically an example output profile of light intensity as a function of angle. Profiles like that shown in  FIG. 7  are typical of many light emitting diode (LED) sources, for example. Such a source may be positioned as shown in  FIG. 8  at an angle such that the peak emission angle is directed outside the field of view on the side of the field of view away from the source (the far side). When such positioning is used the emission at angle θ far  may be higher than that at θ near , which may compensate for the fact that the illumination intensity in W/m 2  is higher on the near side of the field of view compared to the far side because the distance d near  is lower than d far . Positions of light sources  32  may be varied (e.g. varying incident angles and/or distances from painting  2 ) may be used to reduce intensity variations across the field of view. 
     In some embodiments system  20  comprises one or more sensors for monitoring environmental conditions such as humidity, temperature, etc. within cavity  21 . If environmental conditions that may potentially damage painting  2  are detected, then system  20  may, for example, cease operation of system  20 , activate a warning system such as an alarm, activate a correction system such as a cooling fan, etc. 
     System  20  may be portable and/or stationary. In some embodiments system  20  is designed to be mounted at a permanent location. In some embodiments system  20  is designed for portability. For example, system  20  may comprise wheels that may be used to transport system  20  from place to place or system  20  may be made so that it can be readily disassembled into readily portable components. 
     Another aspect of the invention provides a method for generating a color map image of a painting. As described elsewhere herein, the color map image represents color values as a function of position within the painting. To generate the color map image, images of the painting may be acquired, processed to remove specular highlights and/or shadows and registered together. Images of the painting may be acquired, for example, as described above. 
       FIG. 9  is a flow chart showing an example method  100  for generating a color map image of painting  2 . Loop  110  acquires a set of images of a region of painting  2 . Each image in the set of images is acquired using different lighting conditions. For example, a different light source  32  may be active for each iteration of loop  110 . 
     Loop  115  acquires a plurality of sets of images. Each set of images in the plurality corresponds to a different region (e.g. image frame) of painting  2 . As described elsewhere herein, adjacent regions being imaged may overlap. For example, adjacent regions may overlap by approximately 50%. 
     In step  111  an image of a region is acquired. In step  112  method  100  determines whether the region should be imaged using another lighting condition. In some embodiments block  112  produces a NO result after loop  110  has repeated N times when N is the number of different light sources  32 . In some embodiments a predetermined sequence of lighting conditions is used for each region. If another lighting condition is to be used, step  114  selects the next lighting condition. Otherwise method  100  proceeds to step  116 . 
     Step  116  verifies whether another set of images of painting  2  is to be acquired. If so, a next region of painting  2  to be imaged is selected in step  118 . Step  118  may cause imaging system  23  to be moved to the correct position for imaging the next region. Loop  110  may then be repeated until the required images for the next region have been obtained. Otherwise method  100  proceeds to optional conditioning loop  120 . If conditioning loop  120  is skipped, method  100  proceeds to processing loop  125 . 
     Conditioning loop  120  may be used to reduce image distortions that may be present in the plurality of sets of images (e.g. “condition the sets of images”). For example, conditioning loop  120  may apply processing which corrects for distortions introduced by optical system  31  (e.g. as a result of lens aberrations, etc.). As another example, conditioning loop  120  may apply processing which corrects for color distortions introduced by an imaging sensor of camera  30 . In some embodiments conditioning loop  120  reduces radial distortion, compensates for non-perpendicularity of an optical axis of optical system  31 , calibrates lighting values and/or calibrates color values. Processing techniques for performing these and other conditioning are known. 
     Step  121  conditions a set of images. Step  122  verifies whether another set of images is to be conditioned. If so, step  123  takes a next set of images. In some embodiments each of the plurality of sets of images is conditioned by conditioning loop  120 . 
     Processing loop  125  reduces specular highlights and/or shadows that may be present in each of plurality of sets of images. Step  126  reduces specular highlights and/or shadows that may be present in a set of the plurality of sets of images. In some embodiments reducing specular highlights and/or shadows from a set of images comprises comparing the images of the set of images to identify pixels in the images that appear to be affected by specular reflection and/or pixels in the images that appear to be affected by shadows. The affected pixels may be ignored. A processed image of the region that is substantially free from the effects of specular reflection and/or shadows may be created using non-affected pixels from the set of images. For example, a single combined image may be constructed using pixel values from the images that are not affected by specular reflections or shadows. For pixels where two or more of the images have color values that do not appear to be affected by specular reflections or shadows the two or more color values may be combined to yield the color value for the corresponding pixel in the combined image. 
     Block  127  determines whether another set of images is to be processed using processing loop  125 . If so, step  128  takes a next set of images. 
     Step  130  registers the combined images from each of the processed sets of images together to generate a color map image  102 . In some embodiments step  130  registers each of the combined images of each set of images to generate color map image  102 . 
       FIG. 10  is a flow chart showing example loops  110  and  115  for acquiring a plurality of sets of images of painting  2 . Loops  110 ,  115  may initialize a system for acquiring images of painting  2  (e.g. system  20  described elsewhere herein). Loops  110 ,  115  may also determine how many images are to be acquired per region of painting  2  that is being imaged (e.g. N). Loops  110 ,  115  may also determine how many sets of images of painting  2  are to be acquired (e.g. how many different regions are to be imaged). Loops  110 ,  115  may then be executed to acquire the plurality of sets of images. 
     In step  142  a system for capturing images (e.g. system  20 ) may be initialized. In step  142 , an imaging system (e.g. imaging system  23 ) may also be positioned relative to painting  2  to capture images of a first frame. 
     In step  144  the number of sets of images of painting  2  to be acquired is determined. The number of regions may be determined based on a size of painting  2 , a size of a field of view of an imaging system used to capture images of painting  2  (e.g. imaging system  23 ), an amount by which adjacent regions should overlap, etc. 
     Steps  142  and  144  may be completed in any order. In some embodiments, steps  142  and  144  are completed concurrently. In some embodiments step  142  is completed before step  144 . In some embodiments step  144  is completed before step  142 . 
     In step  146 , loop  115  may confirm that additional sets of images of painting  2  are to be imaged (e.g. images of additional regions of painting  2  are to be acquired). In step  148  the imaging system may be positioned to capture the set of images if the imaging system has not already been previously positioned. In step  150 , loop  110  may confirm that additional images of a region are to be captured (e.g. not all lighting conditions have been used). In step  152  a lighting condition to be used is configured. In step  111 , an image of the current region being imaged is captured using the lighting condition configured in step  152 . 
     Once all sets of images of painting  2  have been acquired, loop  115  may terminate. 
       FIG. 11  illustrates an example conditioning loop  120 . 
     In step  162  geometric correction may be performed. Geometric correction may correct radial distortions (e.g. radial shifting of pixels) that an optical system (e.g. optical system  31  described elsewhere herein) used to capture images of painting  2  may introduce into the images. In some cases, aberrations inherent in optical system  31  distort acquired images. In preferred embodiments the geometric correction is applied equally to each image of each set of the plurality of sets of images of painting  2 . 
     In some embodiments the radial correction is performed using commercially available software such as Photoshop™ or software available from DxO™ Labs of France. In some such embodiments the radial correction may apply a radial correction that has a chromatic dependence. 
     In some embodiments a model for correcting radial distortion is developed by imaging a suitable graticule or other geometric pattern. For example, a graticule may be a pattern of lines having a known spacing (e.g. a square grid of equally-spaced lines). 
     In step  164  acquired images are processed to compensate for any non-perpendicularity of the lens axis relative to painting  2 . The graticule used in step  162  may be used. Such graticule may be conveniently located on an easel that supports painting  2  (e.g. easel  22 ). As another example, the graticule may be located adjacent painting  2 . 
     Step  164  comprises capturing an image of the graticule. The captured image of the graticule may be processed to correct for lens distortion. In some embodiments the captured image of the graticule is processed using step  162  described above. 
     Upon processing of the captured image of the graticule, a suitable affine transformation may be determined. In preferred embodiments application of the affine transformation to the captured image of the graticule results in the captured image of the graticule exactly replicating the lines of the graticule (e.g. making exact squares). The affine transformation is preferably constrained so that a central pixel of the image remains unshifted. The affine transformation may be stored and subsequently applied for conditioning images of painting  2 . Advantageously, if sets of images of painting  2  have been acquired using the same imaging conditions, a single affine transformation may be applied to all of the acquired images. 
     As described elsewhere herein, a set of images of painting  2  may comprise a plurality of images acquired using different lighting conditions. The same affine transformation may be applied to correct all of the images. Doing so may ensure that the pixels of different ones of the images taken with different lighting conditions correspond to the same points on painting  2  after correction. Pixel-to-pixel registration of images taken with a fixed camera position and different lights may be maintained. 
     In step  166 , calibration to account for non-uniformity in the illumination provided by light sources  32  may be performed. Performing step  166  may be desirable even if light emitted from a light source is substantially uniform. 
     In some embodiments a calibration tile is made from a flat and uniform material. The material may be substantially white. Preferably, light scattering exhibited by the material is substantially Lambertian. The material may, for example, be Spectralon™. In some embodiments, a commercially available calibration tile is used. 
     Step  166  may capture an image of the calibration tile (which may be called a “white target”) using the same (or substantially similar) imaging conditions as were used to acquire the images of painting  2 . One image of the calibration tile may be captured for each lighting condition. The images of the calibration tile may be acquired in a non-linear color space such as Adobe 1998. 
     Captured images of the calibration tile may be processed by converting each of the images to a linear color space. When the images are in the Adobe 1998 color space, this may be achieved, for example, by inverting a gamma transformation that forms part of the Adobe 1998 color space. Once the images are in a linear color space, the images may be fitted to a suitable smooth function or filtered using a low-pass image filter to reduce noise. The resulting color-linear intensity images for each light source may be stored. Storing each of the color-linear intensity images may allow images of the painting or of a color calibration image to be processed to account for non-uniformity in the illumination from light sources  32 . For example, each image may be scaled by the appropriate intensity calibration image corresponding to the lighting condition that was used. Once processed, each image may be converted back to a conventional nonlinear color space. In some embodiments each image is converted back to a conventional nonlinear color space by applying a gamma correction. Each color-linear intensity image corresponding to a light source may compensate for any lighting non-uniformity of the light source that may be present across the field of view. 
     Step  166  may be described as a “white balance” correction. 
     In step  168  a color calibration may be performed. The color calibration may be performed by using a color calibration target such as color calibration target  169  shown in  FIG. 11A . 
     Color calibration target  169  comprises a series of differently-colored patches. Color calibration target  169  may, for example, have between 20 and 150 color patches. The color patches may comprise a mixture of neutral and colored pigments. Each of the color patches may have a specific known saturation, lightness and/or hue. In some embodiments, color calibration target  169  is a commercially available color chart such as a chart manufactured by X-Rite of the United States. In some embodiments, color calibration target  169  is a 24-patch Colorchecker Passport™ chart or a 135-patch Colorchecker SG™ chart (both manufactured by X-Rite). 
     Step  168  may capture images of color calibration target  169  using the same conditions (e.g. lighting configuration, camera settings, etc.) that were used to capture the plurality of images of the painting. Considering the relatively small field of view associated with using an optical system comprising a telecentric lens as described elsewhere herein, it may be convenient to image each patch of color calibration target  169  separately. The resulting images may be cropped and tiled together with relatively low accuracy without causing a problem for conventional color calibration software. Additionally, or alternatively, the color values may be extracted from each individual color patch and fed to a profile-generation software module. The resulting color calibration profile, preferably in the form of an ICC profile (the International Color Consortium who publish standards on this subject), may be stored for each lighting condition based on color calibration images taken with that lighting condition. The color correction profiles for a lighting condition may be applied to all images taken with that lighting condition. 
     In some embodiments, generating a color calibration profile for a lighting condition comprises comparing imaged color values of target  169  using the lighting condition with measured color values of target  169  using a calibrated instrument. 
     Conditioning each of the images with loop  120  may produce images that are geometrically calibrated, white balanced and color calibrated. Additionally, each image within a set of images may be registered to one another at a pixel level. Some embodiments may omit one or more steps of loop  120  or may omit loop  120  entirely. In some such embodiments a suitable color map image  102  may nevertheless be generated using the methods described elsewhere herein. 
     The steps of exemplary conditioning loop  120  may be performed in any order. A step of loop  120  may also be performed concurrently with one or more other steps of loop  120  or may be performed alone. 
     Loop  125 , shown in  FIG. 12 , may be used to process the sets of images of painting  2 . Loop  125  compares corresponding lightness values across a set of images to identify any pixels in each of the images that appear to correspond to specular highlights and/or shadows. Loop  125  omits any lightness values identified as corresponding to a specular highlight and/or shadow from consideration when determining color map image  102 . 
     In step  172 , loop  125  is initialized. In step  173 , loop  125  verifies whether a set of images is to be processed. If so, loop  125  may proceed to step  174 . Otherwise loop  125  may terminate. 
     In step  174 , loop  125  verifies that corresponding lightness values within a set of images are to be compared. 
     In step  176 , corresponding lightness values are compared. In some embodiments, step  176  compares corresponding lightness values pixel-by-pixel within a set of images. For example, lightness values of all top left corner pixels in the set of images may be compared. Step  176  may compare lightness values for each pixel in the images. 
     In some embodiments each of the images in a set of images may be converted to a perceptually uniform color space with respect to lightness values. In preferred embodiments each of the images is converted to a CIELAB color space. Optionally all images of painting  2  may be converted to a perceptually uniform color space prior to step  176 . In some embodiments all images of painting  2  are converted to a perceptually uniform color space at the beginning of loop  125 . 
     Lightness values L may be calculated for each of the images in the set of images being processed. If each of the images has been previously converted to a perceptually uniform color space, lightness values L can be directly compared. However, this is not mandatory. If the images are represented in another color space (e.g. a RGB color space) lightness values may be calculated and compared. 
     A threshold lightness difference ΔL T  may be defined. The threshold lightness difference may be used to compare corresponding lightness values for a pixel across each of the conditioned images in a set of images (e.g. comparing a pixel location of a single region). If a pixel value in one of the images differs from other pixel values in the set of images (or differs from a representative value for that pixel, such as an average, mean, median or the like across the set of images) by more than the threshold lightness difference it may be assumed that the pixel value has been affected by a specular highlight or a shadow. Affected pixel values may be discarded or ignored. 
     If all of the corresponding lightness values are within a range ΔL T  of one another (or within a range ΔL T  of a representative lightness value for that pixel), the values may all be accepted. The accepted values may optionally be combined into a single value in the corresponding final output image. In some embodiments accepted values may be obtained by averaging. For example, the accepted values for red, green and blue channels in an Adobe 1998 encoding may be averaged. In some embodiments accepted values may be combined by averaging L, a and b values and reconverting to Adobe 1998 or another desired color space. 
     If the range of L values exceeds ΔL T  more complex processing may be performed. If the highest L value is significantly higher than the next nearest value (e.g. ΔL T &gt;3), the highest L value may be identified as specular and eliminated from consideration in step  178 . In such cases, the specular contribution may be eliminated and the corresponding final output image pixel may be determined by combining the non-eliminated color values from the same pixels in other ones of the set of images which have non-specular values. 
     In some cases outliers may be caused by shadowing of the area of the image corresponding to that pixel for the particular light source, or in the case of a quite steeply sloped surface, the surface of the painting at the location corresponding to the pixel may be inclined by an angle and in a direction that greatly reduces the lightness for a given light source. 
     In some embodiments, excessively dark pixel levels (e.g. pixel values corresponding to shadows) may also be removed in step  178 . If the lowest L value is significantly lower than the next nearest value (e.g. ΔL T &gt;3), the value may be identified as an outlier (e.g. a shadow). In some embodiments, such value is eliminated from contribution to the final output. 
     In some embodiments an elevation map may be used to determine whether a lightness value L higher than ΔL T  is likely to be a specular highlight or shadow. For example, if a pixel being processed is surrounded by brush strokes that have a higher elevation around three edges of the pixel, it is likely that light emitted on the three higher elevation edges will result in a shadow. This information may for example be used to reject shadow values (e.g. values that correspond to lower lightness values) even if the shadow values are a majority of the lightness values for that pixel. 
     If low-lightness outliers have also been eliminated, the corresponding final output image pixel may be determined by combining all non-eliminated values for a pixel that remain after specular and low-lightness values have been eliminated or by selecting a representative one of the non-eliminated values for the pixel. 
     In some embodiments non-eliminated values for a pixel are combined into a single pixel value in a single image corresponding to the set of images by averaging the non-eliminated values for the pixel. 
     In some embodiments, the threshold lightness difference ΔL T  is varied based on how successfully loop  125  removes specular highlights and/or shadows. 
     Loop  125  may compare each set of images pixel-by-pixel. Corresponding values for each pixel that have not been eliminated as a specular highlight or shadow may be combined together into a single processed pixel value. The single processed pixel values may form a processed image of the set of images that was processed effectively removing the effects of identified specular highlights and/or shadows. 
     The processed output images corresponding to regions of painting  2  may be registered together (e.g. step  130  described elsewhere herein). For example, two processed images  182  and  184  (see  FIG. 13A ) may be registered together or stitched (see  FIG. 13B ) to generate a color map image  102  of painting  2  (see  FIG. 13C ). In some embodiments each of the sets of images is registered together. In some embodiments images may be registered together using a commercially available tool such as Photoshop™. 
     In some embodiments a human operator reviews the final composite image. In some embodiments threshold ΔL T  is varied to change effectiveness of loop  125  and/or method  100  for removing specular highlights and/or shadows. In some such embodiments corresponding final composite images are compared to determine how effectively specular highlights and/or shadows were removed. 
     In preferred embodiments scanner  28  collects color data corresponding to color values of painting  2 . Obtaining the color data may comprise measuring reflectance of light of a plurality of wavelengths at points of painting  2 . The collected color data may be used in combination with elevation data to produce a reproduction of painting  2 . As described elsewhere herein, scanner  28  may comprise three single-mode lasers (e.g. 450, 532 and 638 nm lasers). Scanning painting  2  with such laser scanner may collect color data only corresponding to wavelengths of the single-mode lasers. Color data collected by the laser scanner may therefore be ambiguous regarding the precise color of a point on painting  2 . For example, a specific color measurement by scanner  28  may correspond to any of a plurality of different spectral power distributions. The different spectral power distributions may appear differently to the human eye. Advantageously, color data represented by generated color map image  102  may be processed to refine color data collected by scanner  28 . 
       FIG. 14  is a flow chart showing an example method  200  for refining color data collected by scanner  28 . 
     In step  202  painting  2  is scanned with a laser scanner (e.g. scanner  28 ). In some embodiments the laser scanner serially scans painting  2 . In some embodiments painting  2  is scanned at two complementary angles of incidence (as described elsewhere herein). For example, a line of painting  2  may be scanned at a first angle. The line of painting  2  may then be scanned at a second complementary angle before the laser scanner proceeds to scan another line of painting  2 . In some embodiments the laser scanner scans the painting at angles of 20 degrees and −20 degrees relative to a normal vector of painting  2 . 
     Scanning painting  2  with the laser scanner may collect point cloud data corresponding to the painting. Color and/or elevation maps may be generated from the point cloud data. In some embodiments the color and/or elevation maps have a resolution of 254 dpi (100 μm pixels) or finer. 
     The laser color data may be processed to reduce distortions that may be present in the data. 
     In step  204  the laser color data is processed to reduce shading effects. Shading effects can result when the optical path length from a pixel location on a painting to a light detector of the optical detector is different for different pixel locations and/or when the angle of inclination of the surface of the painting relative to an angle of incidence of laser light is different for different pixels locations. 
     Shading effects may, for example, be reduced for each pixel by scaling color values represented by each pixel. The laser color data may, for example, be scaled according to Lambert&#39;s law. In some embodiments the color values are scaled by dividing the color measurements represented by a pixel by a cosine of an angle between a surface normal of the painting at a point represented by the pixel value and a direction vector. The direction vector may extend from the point represented by the pixel to a center of an optical aperture corresponding to a detector configured to collect scattered light during the laser scanning. The computed quotient may then be multiplied by a square of a scalar distance between the point represented by the pixel to the center of the optical aperture of the detector. In some embodiments reflectance is normalized. Reflectance may, for example, be normalized by dividing the color measurements corresponding to the painting by color values measured for an ideal diffuse reference target with unit reflectance. Preferably, the color values corresponding to the ideal diffuse reference target are scaled as described herein. 
     In step  206  specular highlights are removed from the laser color data. If two laser scans with complementary angles have been performed, data from the scans may be registered and compared. Where laser color data for one angle of incidence is lighter than the laser color data for a complementary angle of incidence the lighter data may be assumed to correspond to specular reflection and may be ignored. 
     Steps  204  and  206  may be performed in any order. In some embodiments steps  204  and  206  are performed concurrently. 
     In some embodiments calibration scans may be performed before and/or after scanning of painting  2 . The calibration scans may determine a black point and/or color channel gains. The calibrations scans may, for example, comprise scanning one or more calibration targets (e.g. a plurality of flat Spectralon™ targets that provide varying reflectance factors). 
     In step  208  processed laser data (e.g. an image representing color values of painting  2 ) is transformed into a suitable color space. In some embodiments a matrix transformation (3×3 in the case where the laser scanner scans at three wavelengths) converts the processed laser data (e.g. the processed laser RGB signals) to laser color values in the desired color space. The color space may for example be a tristimulus color space such as CIEXYZ. Coefficients for the matrix transformation may be derived from a least-squares regression of a suitably large number of measured reflection spectra of real objects having known colors. In some embodiments the transformation produces an exact color reproduction comprising chromaticity and/or absolute luminance identical to the known colors of each object. The CIEXYZ laser color values may then be converted to another color format for further processing such as the Adobe 1998 color space. 
     Steps  210  to  216  use the images obtained by imaging device  23  (e.g. color map  102 ) to adjust colors. These steps can help to correct for the fact that different pigments which appear different to the human eye may have the same color as measured by the laser scanner. Fortunately, in any particular painting  102  it is likely that pixels which provide the same laser color values are colored with the same pigment. Steps  210  to  216  may be performed in a suitable color space. In some cases the color space is an RGB color space such as the Adobe 1998 color space. 
     The converted laser data may be registered with a generated color map image  102  in step  210 . This step allows direct comparison of colors detected by scanner and imaging device  23  at a pixel level. In some embodiments localized stretching of pixels (or fractions of pixels) is performed to achieve registration. In some embodiments correlations between sets of pixels of the laser data and sets of pixels of image  102  are analyzed to determine shifts necessary to align the pixels to within a fraction of the pitch of the pixels. In some embodiments black and/or white pixels of the laser data are matched with black and/or white pixels of image  102 . In some such embodiments each channel of the laser data may be scaled to match a corresponding channel in image  102  at, for example, 0.5 and 99.95 percentile points. 
     A look-up table (LUT) for correcting color values in the laser data may be populated using color data from color map image  102  and the corresponding laser color values. Imaging device  23  may yield inaccurate color data for pixels that are in shadows, in parts of painting  2  that are steep or the like. Including such pixels in determining the values for the LUT could therefore result in significant errors. To avoid this, pixels in color map image  102  which are suspicious, for example because they correspond to steeply sloping parts of painting  2  or areas that may be in shadow or the like may be excluded from calculation of the LUT values (e.g. by being masked out). Elevation contours of painting  2  may, for example, be determined from collected elevation data. In step  212 , pixels of image  102  are masked. 
     The masked pixels of image  102  may, for example, comprise pixels representing photometric shading. For example, any pixel corresponding to a point on painting  2  for which a surface normal is more than a threshold angle from a viewing direction (e.g. 30 degrees) may be masked. 
     Additionally, or alternatively, pixels representing cast shadows may be masked out. In some embodiments pixels are identified as corresponding to a cast shadow by comparing a surface gradient of a pixel to an illumination gradient of the pixel. If the surface gradient is more negative than the illumination gradient, the pixel may be masked out for corresponding to a cast shadow. In some embodiments a shadow mask is separately generated for each laser scan (e.g. if two laser scans were performed, two shadow masks may be generated). The generated shadow masks may optionally be combined into a single shadow mask that may be applied to color map image  102  to exclude pixels corresponding to cast shadows. 
     Additionally, or alternatively, a presence of specular highlights may be further reduced by masking out pixels identified as possibly corresponding to specular highlights. Elevation data may, for example, be used to determine pixel locations likely to represent specular highlights. In some embodiments specular peaks are modeled using a Lorentzian function. In some such embodiments, pixels corresponding to illumination angles within a threshold cone in radius about a specular peak may be masked out. The threshold cone may, for example, be represented by a parameter β min , where β min  is a suitable angle such as 20 degrees. In some embodiments it is unnecessary to mask out specular highlights because specular highlights have been reduced by an acceptable amount when generating color map image using the methods described elsewhere herein. 
     The size of the LUT may be chosen to be of a size such that a majority of LUT cells can contain data taken directly from non-masked pixels of the reference image. Other cells in the LUT may be filled by calculating values using a suitable fitting routine. 
     In step  214 , the LUT is populated. A value of the laser data may be used as a key to address the LUT table. Populating the LUT may, for example, comprise taking a median of all color values from image  102  that correspond to pixels in the laser color data having a given color value. This may, for example, comprise comparing a color value of a pixel of the laser data to a corresponding pixel of image  102 . A median value may then be determined of all un-masked color values in image  102  that are substantially similar to the color value of the pixel. Any empty points within an image gamut in the LUT may be populated by taking a median of non-empty nearest neighbors. Any empty points outside the gamut typically play a limited role and may optionally be filled with corresponding gray scale values. In some embodiments a 3×3×3 median filter is applied to all values in the LUT. 
     In step  216  color values represented by pixels of the laser data may be corrected. Color values represented by pixels of the laser data may, for example, be corrected by retrieving corresponding color values from the LUT. 
     Color image  220  comprising corrected laser color data may be combined with elevation data to produce a high-quality digital reproduction of painting  2 . 
     Typically a generated LUT is specific to a set of pigments used by an artist to paint a specific painting. However, in some cases, an artist may choose to paint a series of paintings using the same set of pigments. In such cases, one LUT may be used to correct laser data for each of the paintings in the series. This may, for example, reduce processing time as a LUT must be generated only for the first painting in the series. Alternatively, a set of images  102  corresponding to each of the paintings in the series may be used to generate a LUT with more accurate color values. 
     The systems and methods described herein may be applied to acquire high quality digital representations of any painting or drawing and/or to create replicas of the painting or drawing. 
     Example Use Scenario 
     An owner (e.g. a private collector, a museum, an art gallery, etc.) of a fine art painting may decide that the painting should be safely stored. However, safely storing the painting (e.g. in a vault) would deprive the owner and/or others from viewing the painting. The owner may wish to obtain a faithful reproduction of the painting that may be displayed. 
     The owner may arrange for a system  20  to be brought to a location where the painting may be scanned or for the painting to be brought to a location of a system  20 . 
     The painting may be scanned by system  20  as described herein to obtain digital data that fully describes the color and 3D form of the painting as described herein. System  20  may generate an elevation map and a corresponding color map image of the painting. Preferably a final color map image to be used when producing a reproduction is generated by correcting laser color data using a color map image generated from photographs of the painting as described elsewhere herein. The elevation map image and the color map image of the painting may be communicated to a 3D printer. The 3D printer can then produce a 3D reproduction of the painting based on the communicated data. 
     In some cases, the 3D printer and system  20  are at the same location. In some cases, the 3D printer and system  20  are at different locations. 
     In some cases the elevation map and/or color map image of the painting may be stored. Advantageously this allows for additional reproductions of the painting to be reproduced later on without having to retrieve the original painting from its safe storage location. The stored elevation map and/or color map image may also be used to generate digital renderings of the painting. 
     In some cases the painting is inspected prior to being positioned within system  20 . If the painting is deemed to be fragile (e.g. having a high risk of being damaged if placed within system  20 ), the painting may not be positioned within system  20 . Additionally, or alternatively, damaged sections of the painting may be noted. In some cases the damaged sections are corrected in the generated elevation map and/or color map image. In some cases software interpolates values for the damaged sections. In some cases an operator manually inputs values for the damaged sections. 
     In some cases an expert compares the reproduction of the painting to the original painting. If the produced reproduction does not faithfully reproduce the original painting, a new reproduction may be produced. 
     Interpretation of Terms 
     Unless the context clearly requires otherwise, throughout the description and the
         “comprise”, “comprising”, and the like are to be construed in an inclusive sense, as opposed to an exclusive or exhaustive sense; that is to say, in the sense of “including, but not limited to”;   “connected”, “coupled”, or any variant thereof, means any connection or coupling, either direct or indirect, between two or more elements; the coupling or connection between the elements can be physical, logical, or a combination thereof;   “herein”, “above”, “below”, and words of similar import, when used to describe this specification, shall refer to this specification as a whole, and not to any particular portions of this specification;   “or”, in reference to a list of two or more items, covers all of the following interpretations of the word: any of the items in the list, all of the items in the list, and any combination of the items in the list;   the singular forms “a”, “an”, and “the” also include the meaning of any appropriate plural forms.       

     Words that indicate directions such as “vertical”, “transverse”, “horizontal”, “upward”, “downward”, “forward”, “backward”, “inward”, “outward”, “vertical”, “transverse”, “left”, “right”, “front”, “back”, “top”, “bottom”, “below”, “above”, “under”, and the like, used in this description and any accompanying claims (where present), depend on the specific orientation of the apparatus described and illustrated. The subject matter described herein may assume various alternative orientations. Accordingly, these directional terms are not strictly defined and should not be interpreted narrowly. 
     Embodiments of the invention may be implemented using specifically designed hardware, configurable hardware, programmable data processors configured by the provision of software (which may optionally comprise “firmware”) capable of executing on the data processors, special purpose computers or data processors that are specifically programmed, configured, or constructed to perform one or more steps in a method as explained in detail herein and/or combinations of two or more of these. Examples of specifically designed hardware are: logic circuits, application-specific integrated circuits (“ASICs”), large scale integrated circuits (“LSIs”), very large scale integrated circuits (“VLSIs”), and the like. Examples of configurable hardware are: one or more programmable logic devices such as programmable array logic (“PALs”), programmable logic arrays (“PLAs”), and field programmable gate arrays (“FPGAs”)). Examples of programmable data processors are: microprocessors, digital signal processors (“DSPs”), embedded processors, graphics processors, math co-processors, general purpose computers, server computers, cloud computers, mainframe computers, computer workstations, and the like. For example, one or more data processors in a control circuit for a device may implement methods as described herein by executing software instructions in a program memory accessible to the processors. 
     Processing may be centralized or distributed. Where processing is distributed, information including software and/or data may be kept centrally or distributed. Such information may be exchanged between different functional units by way of a communications network, such as a Local Area Network (LAN), Wide Area Network (WAN), or the Internet, wired or wireless data links, electromagnetic signals, or other data communication channel. 
     For example, while processes or blocks are presented in a given order, alternative examples may perform routines having steps, or employ systems having blocks, in a different order, and some processes or blocks may be deleted, moved, added, subdivided, combined, and/or modified to provide alternative or subcombinations. Each of these processes or blocks may be implemented in a variety of different ways. Also, while processes or blocks are at times shown as being performed in series, these processes or blocks may instead be performed in parallel, or may be performed at different times. 
     In addition, while elements are at times shown as being performed sequentially, they may instead be performed simultaneously or in different sequences. It is therefore intended that the following claims are interpreted to include all such variations as are within their intended scope. 
     Aspects of the invention may also be provided in the form of a program product. The program product may comprise any non-transitory medium which carries a set of computer-readable instructions which, when executed by a data processor, cause the data processor to execute a method of the invention. Program products according to the invention may be in any of a wide variety of forms. The program product may comprise, for example, non-transitory media such as magnetic data storage media including floppy diskettes, hard disk drives, optical data storage media including CD ROMs, DVDs, electronic data storage media including ROMs, flash RAM, EPROMs, hardwired or preprogrammed chips (e.g., EEPROM semiconductor chips), nanotechnology memory, or the like. The computer-readable signals on the program product may optionally be compressed or encrypted. 
     In some embodiments, aspects of the invention may be implemented in software. For greater clarity, “software” includes any instructions executed on a processor, and may include (but is not limited to) firmware, resident software, microcode, and the like. Both processing hardware and software may be centralized or distributed (or a combination thereof), in whole or in part, as known to those skilled in the art. For example, software and other modules may be accessible via local memory, via a network, via a browser or other application in a distributed computing context, or via other means suitable for the purposes described above. 
     Where a component (e.g. a software module, processor, assembly, device, circuit, etc.) is referred to above, unless otherwise indicated, reference to that component (including a reference to a “means”) should be interpreted as including as equivalents of that component any component which performs the function of the described component (i.e., that is functionally equivalent), including components which are not structurally equivalent to the disclosed structure which performs the function in the illustrated exemplary embodiments of the invention. 
     Specific examples of systems, methods and apparatus have been described herein for purposes of illustration. These are only examples. The technology provided herein can be applied to systems other than the example systems described above. Many alterations, modifications, additions, omissions, and permutations are possible within the practice of this invention. This invention includes variations on described embodiments that would be apparent to the skilled addressee, including variations obtained by: replacing features, elements and/or acts with equivalent features, elements and/or acts; mixing and matching of features, elements and/or acts from different embodiments; combining features, elements and/or acts from embodiments as described herein with features, elements and/or acts of other technology; and/or omitting combining features, elements and/or acts from described embodiments. 
     Various features are described herein as being present in “some embodiments”. Such features are not mandatory and may not be present in all embodiments. Embodiments of the invention may include zero, any one or any combination of two or more of such features. This is limited only to the extent that certain ones of such features are incompatible with other ones of such features in the sense that it would be impossible for a person of ordinary skill in the art to construct a practical embodiment that combines such incompatible features. Consequently, the description that “some embodiments” possess feature A and “some embodiments” possess feature B should be interpreted as an express indication that the inventors also contemplate embodiments which combine features A and B (unless the description states otherwise or features A and B are fundamentally incompatible). 
     It is therefore intended that the following appended claims and claims hereafter introduced are interpreted to include all such modifications, permutations, additions, omissions, and sub-combinations as may reasonably be inferred. The scope of the claims should not be limited by the preferred embodiments set forth in the examples, but should be given the broadest interpretation consistent with the description as a whole.