Patent Publication Number: US-11044396-B2

Title: Image processing apparatus for calculating a composite ratio of each area based on a contrast value of images, control method of image processing apparatus, and computer-readable storage medium

Description:
BACKGROUND OF THE INVENTION 
     Field of the Invention 
     The present invention relates to an image processing apparatus that composites a plurality of images having different in-focus positions, and to an image pickup apparatus, a control method of the image processing apparatus, and a computer-readable storage medium therefor. 
     Description of the Related Art 
     In a case where image pickup for a plurality of objects having greatly different distances therebetween is performed or in a case where image pickup for an object that is long in a depth direction is performed, only a part of the object may be brought into focus because the depth of field is insufficient. To address this issue, Japanese Patent Application Laid-Open No. 2015-216532 discusses a depth compositing technology. In this technology, a plurality of images having different in-focus positions is picked up, and only in-focus areas are extracted from the respective images and composited into one image, so that a composite image in which focus is achieved in the entire imaging area is generated. 
     However, when the above-described depth compositing method is used, there is a case where a defect appears in a composite image because a composite ratio is not uniform on the boundary of an object and a composite boundary is thereby made noticeable. Meanwhile, it is expected that the above-described issue will be addressed by blurring the entire composite image, but if there is a portion where it is desirable to express details, the details of this portion may be lost. 
     SUMMARY OF THE INVENTION 
     The present invention is directed to an image processing apparatus that can achieve a balance between details of an object and a smooth change in composite ratio between neighboring pixels, in an image composited using a plurality of images having different in-focus positions. 
     According to an aspect of the present invention, an image processing apparatus includes at least one memory configured to store instructions, and at least one processor in communication with the at least one memory and configured to execute the instructions to generate a composite ratio for composition of a plurality of images, for each area of the plurality of images, based on a contrast value of the area, conduct an adjustment to the composite ratio, and generate a composite image by the plurality of images based on a composite ratio after the adjustment. For at least one image of a part of the plurality of images, a relationship (i.e., gradient, slope, etc.,) between the composite ratios of neighboring areas becomes more smooth after the adjustment. For example, a gradient and/or a slope of the composite ratios of neighboring areas of one image becomes more smooth after the adjustment. Furthermore, the composite ratio spreads more widely in an area than in another area after the adjustment. A degree of the adjustment of a first area having a first contrast value is higher than a degree of the adjustment of a second area having a second contrast value that is higher than the first contrast value. 
     According to the configuration of the present invention, it is possible to provide an image processing apparatus that achieves a smooth change in composite ratio between neighboring pixels while maintaining details of an object, in an image composited using a plurality of picked-up images having different in-focus positions. 
     Further features of the present invention will become apparent from the following description of exemplary embodiments with reference to the attached drawings. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a block diagram illustrating a structure of a digital camera according to an exemplary embodiment of the present invention. 
         FIG. 2  is a flowchart illustrating generation of a composite image in the exemplary embodiment of the present invention. 
         FIG. 3  is a flowchart illustrating image pickup in the exemplary embodiment of the present invention. 
         FIG. 4  is a flowchart illustrating alignment in the exemplary embodiment of the present invention. 
         FIG. 5  is a flowchart illustrating composition of images in the exemplary embodiment of the present invention. 
         FIG. 6  is a flowchart illustrating generation of a composite map in the exemplary embodiment of the present invention. 
         FIG. 7  is a block diagram illustrating integration of composite ratios in the exemplary embodiment of the present invention. 
         FIG. 8  is a diagram illustrating an example of a relationship between an integration ratio α and a contrast value C(x,y) in the exemplary embodiment of the present invention. 
     
    
    
     DESCRIPTION OF THE EMBODIMENTS 
     An exemplary embodiment of the present invention will be described in detail below with reference to the attached drawings. 
       FIG. 1  is a block diagram illustrating a structure of a digital camera serving as an image processing apparatus according to an exemplary embodiment of the present invention. A digital camera  100  can pick up a still image, and record information indicating an in-focus position. The digital camera  100  can also perform calculation of a contrast value and composition of images. Further, the digital camera  100  can perform enlargement processing or reduction processing, on an image stored upon pickup or an image input from outside. 
     A control unit  101  is, for example, a signal processor such as a central processing unit (CPU) or a micro processing unit (MPU). The control unit  101  controls each part of the digital camera  100  while reading out a program stored beforehand in a read only memory (ROM)  105  to be described below. For example, as will be described below, the control unit  101  issues a command for each of start and end of image pickup to an image pickup unit  104  to be described below. Alternatively, the control unit  101  issues a command for image processing to an image processing unit  107  to be described below, based on the program stored in the ROM  105 . A command provided by a user is input into the digital camera  100  by an operation unit  110  to be described below, and reaches each part of the digital camera  100  via the control unit  101 . 
     A drive unit  102  incudes a motor, and mechanically operates an optical system  103  to be described below, based on a command of the control unit  101 . For example, the drive unit  102  adjusts a focal length of the optical system  103  by moving the position of a focus lens included in the optical system  103  based on a command of the control unit  101 . 
     The optical system  103  includes a zoom lens, the focus lens, and an iris diaphragm. The iris diaphragm is a mechanism for adjusting the quantity of light passing therethrough. It is possible to change an in-focus position by changing a lens position. 
     The image pickup unit  104  is a photoelectric conversion element, and photoelectrically converts an incident light signal into an electrical signal. For example, a sensor such as a charge-coupled device (CCD) sensor or a complementary metal oxide semiconductor (CMOS) sensor is applicable to the image pickup unit  104 . The image pickup unit  104  has a moving image pickup mode, and can pick up each of a plurality of temporally consecutive images, as each frame of a moving image. 
     The ROM  105  is a nonvolatile read-only memory serving as a storage medium. The ROM  105  stores, in addition to a program for an operation of each block included in the digital camera  100 , a parameter necessary for the operation of each block. A random access memory (RAM)  106  is a rewritable volatile memory. The RAM  106  is used as a temporary storage area for data output in the operation of each block included in the digital camera  100 . 
     The image processing unit  107  performs various kinds of image processing including white balance adjustment, color interpolation, and filtering, for an image output from the image pickup unit  104  or data of an image signal recorded in an internal memory  109  to be described below. In addition, the image processing unit  107  performs compression processing in a standard such as Joint Photographic Experts Group (JPEG), for data of an image signal picked up by the image pickup unit  104 . 
     The image processing unit  107  includes an integrated circuit (an application-specific integrated circuit (ASIC)) in which circuits each performing specific processing are integrated. Alternatively, the control unit  101  may perform some or all of the functions of the image processing unit  107 , by reading a program from the ROM  105  and performing processing based on this program. In a case where the control unit  101  performs all the functions of the image processing unit  107 , it is not necessary to provide the image processing unit  107  as hardware. 
     A display unit  108  is a liquid crystal display or an organic electroluminescence (EL) display for displaying an image temporarily stored in the RAM  106 , an image stored in the internal memory  109  to be described below, or a setting screen of the digital camera  100 . 
     The internal memory  109  is an area for recording an image picked up by the image pickup unit  104 , an image processed by the image processing unit  107 , and information such as information indicating an in-focus position in image pickup. Another type of device such as a memory card can be used in place of the internal memory. 
     The operation unit  110  is, for example, a button, a switch, a key, and a mode dial provided in the digital camera  100 , or a touch panel that the display unit  108  doubles as. A command provided by the user reaches the control unit  101  via the operation unit  110 . 
       FIG. 2  is a flowchart illustrating generation of a composite image in the present exemplary embodiment. In step S 201 , the image pickup unit  104  picks up a plurality of images having different in-focus positions. In step S 202 , the control unit  101  aligns the plurality of images picked up by the image pickup unit  104  in step S 201  so that angles of view coincide with one another or at least partially overlap each other. In step S 203 , the image processing unit  107  generates a composite image by performing composition of the aligned images. Each of these steps will be described in detail below. 
       FIG. 3  is a flowchart illustrating the image pickup in step S 201  in the present exemplary embodiment. 
     In step S 301 , the control unit  101  sets a focus position. For example, the user designates an in-focus position via the touch panel that the display unit  108  doubles as, and designates a plurality of focus positions at regular intervals along an optical axis direction of a focus position corresponding to the in-focus position. At the same time, the control unit  101  determines an image pickup sequence in distance order, for the set focus positions. 
     In step S 302 , the image pickup unit  104  picks up an image at the top focus position in the image pickup sequence among focus positions not used for image pickup, among the focus positions set in step S 301 . 
     In step S 303 , the control unit  101  determines whether image pickup has been performed for all the focus positions set in step S 301 . In a case where the image pickup has been performed for all the focus positions (YES in step S 303 ), the processing in the flowchart illustrated in  FIG. 3  ends. In a case where there is a focus position not used for the image pickup (NO in step S 303 ), the processing returns to step S 302 . 
     The above-described image pickup method can be performed a less number of times using a camera such as a multiple lens camera including a plurality of optical systems  103  and a plurality of image pickup units  104 . 
       FIG. 4  is a flowchart illustrating the alignment in step S 202  in the present exemplary embodiment. 
     In step S 401 , the control unit  101  acquires a reference image for alignment from the images picked up by the image pickup unit  104  in step S 201 . The reference image for the alignment is an image at the top in the image pickup sequence. Alternatively, the reference image for the alignment can be an image having the narrowest angle of view among the picked-up images, because performing image pickup while changing the focus position causes slight variation in the angle of view between the picked-up images. 
     In step S 402 , the control unit  101  acquires a target image for alignment processing. The target image is any image except for the reference image acquired in step S 401  and this image has not undergone the alignment processing. If the reference image is the image at the top in the image pickup sequence, the control unit  101  may acquire the target images sequentially in the image pickup sequence. 
     In step S 403 , the control unit  101  calculates an amount of positional misalignment between the reference image and the target image. An example of a method for this calculation will be described below. First, the control unit  101  sets a plurality of blocks in the reference image. It is preferable that the control unit  101  set the plurality of blocks so that the sizes of the respective blocks are equal. Next, the control unit  101  sets a range of the target image at the same position as that of each block in the reference image, as a search range. The set range is wider than the block in the reference image. The control unit  101  calculates a corresponding point at which a sum of absolute difference (SAD) of luminance with respect to the block in the reference image is minimized, in the search range in each of the target images. The control unit  101  calculates, as a vector, the positional misalignment in step S 403  based on the center of the block in the reference image and the above-described corresponding point. The control unit  101  can use, besides the SAD, a sum of squared differences (SSD) and normalized cross correlation (NCC), in the calculation of the corresponding point described above. 
     In step S 404 , the control unit  101  calculates a transformation coefficient based on the amount of positional misalignment between the reference image and the target image. The control unit  101  uses, for example, a projective transformation coefficient as the transformation coefficient. However, the transformation coefficient is not limited to the projective transformation coefficient. An affine transformation coefficient or a simplified transformation coefficient based on only a horizontal and vertical shift can be used. 
     In step S 405 , the image processing unit  107  performs transformation for the target image, using the transformation coefficient calculated in step S 404 . 
     For example, the control unit  101  can perform the transformation, using the following expression (1). 
                     I   ′     =       (           x   ′               y   ′             1         )     =     AI   =       (         a       b       c           d       e       f           0       0       1         )     ·     (         x           y           1         )                   (   1   )               
In the expression (1), (x′,y′) represents coordinates after the transformation, and (x,y) represents coordinates before the transformation. A matrix A represents the transformation coefficient calculated by the control unit  101  in step S 404 .
 
     In step S 406 , the control unit  101  determines whether the alignment has been performed for all the images except for the reference image. In a case where the alignment has been performed for all the images except for the reference image (YES in step S 406 ), the processing in this flowchart ends. In a case where there is an unprocessed image (NO in step S 406 ), the processing returns to step S 402 . 
       FIG. 5  is a flowchart illustrating the image composition in step S 203  in the present exemplary embodiment. 
     In step S 501 , the image processing unit  107  calculates a contrast value for each of the images after the alignment (including the reference image). For example, the contrast value is calculated by the following method. First, the image processing unit  107  calculates a luminance Y, using the following expression (2), based on color signals Sr, Sg, and Sb of each pixel.
 
 Y= 0.299 Sr+ 0.587 Sg+ 0.114 Sb   (2)
 
     Next, the image processing unit  107  calculates a contrast value I in a pixel of interest, using a Sobel filter, in a matrix L of the luminance Y in a 3×3 pixel range including the pixel of interest, as expressed in the following expressions (3) to (5). 
     
       
         
           
             
               
                 
                   
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     The above-described method for calculating the contrast value is only an example. For example, an edge detection filter such as a Laplacian filter or a bandpass filter for passing a predetermined bandwidth can be used for the filter. 
     In step S 502 , the image processing unit  107  generates a composite map. The image processing unit  107  calculates a composite ratio by comparing the contrast values of the pixels at the same positions in the respective images after the alignment. 
     For example, the image processing unit  107  applies a composite ratio of 100% to a pixel having the highest contrast value, among the pixels at the same positions. 
     It is possible to calculate a composite ratio of a pixel located at coordinates(x,y) in the mth image among an M number of images, using the following expression (6). 
     
       
         
           
             
               
                 
                   
                     
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     In step S 503 , the image processing unit  107  corrects the composite map calculated in step S 502 . 
       FIG. 6  is a flowchart illustrating the correction of the composite map in step S 503 . 
     In step S 601 , the image processing unit  107  performs filter processing for the composite ratio corresponding to each pixel calculated in step S 502 . The types of the filter include a MAX filter that outputs a maximum value, for composite ratios within a reference range defined by the number of taps, or a mean value filter. In addition, in step S 601 , the image processing unit  107  acquires a plurality of pieces of data each having a smoothed composite ratio, by separately applying the filters that vary in the number of taps to the composite ratio. Here, for convenience of description, two types of filter, i.e., filters N[ 0 ] and N[ 1 ] that vary in smoothing level are applied, but the number of the filters is not limited to two. The number of taps of the filter N[ 0 ] is less than that of the filter N[ 1 ]. In other words, the reference range of the filter N[ 0 ] is smaller than that of the filter N[ 1 ]. The filter N[ 0 ] can be of a through output type (input and output are the same signals). Because the image processing unit  107  applies the filters, the composite ratio calculated in step S 502  can be extended to surroundings. In a case where sharp change in the composite ratio between the pixels occurs, the application of the filters by the image processing unit  107  can smooth the change in the composite ratio between the pixels. 
     In step S 602 , the image processing unit  107  integrates the composite ratios after the plurality of filters is applied in step S 601 . 
       FIG. 7  is a block diagram illustrating the integration of the composite ratios in the present exemplary embodiment. The image processing unit  107  applies each of the filter N[ 0 ] and the filter N[ 1 ] to a composite ratio Am(x,y). Then, the image processing unit  107  integrates the composite ratios after the application of these two kinds of filters based on the contrast values. In the integration, the integration ratio of the composite ratio after the application of the filter having the small number of taps is higher in an area where the contrast value is higher, and the integration ratio of the composite ratio after the application of the filter having the large number of taps is higher in an area where the contrast value is lower. The larger the number of the taps of the filter is, the more the screen after the application of the filter is blurred. Therefore, the integration ratio of the composite ratio after the application of the filter having the small number of taps is higher in the area where the contrast value is higher, so that details in the area where the contrast value is higher can be maintained. In contrast, the integration ratio of the composite ratio after the application of the filter having the large number of taps is higher in the area where the contrast value is lower, so that suppression of a defect after composition in the area where the contrast value is lower can be expected. Furthermore, the composite ratio spreads more widely in an area than in another area after the adjustment. 
     Table 1 represents the relationship here among the integration ratio, each of the area contrast value, and the number of taps. 
     
       
         
           
               
               
               
             
               
                 TABLE 1 
               
               
                   
               
               
                 Integration Ratio 
                 Number of Taps: Small 
                 Number of Taps: Large 
               
               
                   
               
             
            
               
                 Contrast value: Low 
                 Low 
                 High 
               
               
                 Contrast value: High 
                 High 
                 Low 
               
               
                   
               
            
           
         
       
     
     For example, in a case where the composite ratio after the application of the filter N[ 0 ] is a composite ratio Am0(x,y) and the composite ratio after the application of the filter N[ 1 ] is a composite ratio Am1(x,y), a corrected composite ratio Bm(x,y) can be calculated by the following expression (7).
 
 Bm ( x,y )=(1−α)× Am 0( x,y )+α× Am 1( x,y )  (7)
 
A ratio α used in the expression (7) is an integration ratio and can be calculated from a contrast value C(x,y). For the contrast value C(x,y) here, any of a maximum value, an additional value, and a weighted average value of the contrast values of coordinates (x,y) of a plurality of images can be used.
 
       FIG. 8  is a graph illustrating an example of the relationship between the integration ratio α and the contrast value C(x,y) in the present exemplary embodiment. 
     In step S 603 , the control unit  101  determines whether all the images are processed. In a case where there is an unprocessed image (NO in step S 603 ), the processing returns to step S 601  in which the image processing unit  107  performs the filter processing for the unprocessed image. 
     Finally, the processing proceeds to step S 604 . In step S 604 , the image processing unit  107  recalculates the composite ratio. Here, the image processing unit  107  performs normalization for the corrected composite ratio Bm(x,y), and thereby calculates a composite ratio Bm′(x,y) to be finally used for generation of a composite image. Specifically, the image processing unit  107  performs the calculation based on the following expression (8). 
     
       
         
           
             
               
                 
                   
                     
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     In the expression (8), M represents the number of images, and (x,y) represents the coordinates. The normalization is performed based on the expression (8), so that 1 is determined as the sum of the composite ratios Bm′(x,y) of the same coordinates after the alignment. 
     In step S 504 , the image processing unit  107  generates a composite image based on the following expression (9). 
     
       
         
           
             
               
                 
                   
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     In the expression (9), Ik(x,y) represents the pixel value of the coordinates(x,y) of the kth image, and O(x,y) represents the pixel value of the coordinates (x,y) of the composite image. 
     According to the present exemplary embodiment, when a depth composite image is generated, it is possible to reduce defects of the composite image while maintaining details of the image. 
     The exemplary embodiment is described above, based on the digital camera for personal use. However, the present exemplary embodiment is applicable to other types of apparatuses such as a portable, a smartphone, and a network camera connected to a server, as far as the apparatus is equipped with a depth compositing function. Alternatively, a part of the above-described processing can be performed by an apparatus such as a portable, a smartphone, or a network camera connected to a server. 
     According to the configuration of the present exemplary embodiment, it is possible to provide an image processing apparatus that smooths a change in a composite ratio between neighboring pixels while maintaining details of an object, in a composite image of a plurality of picked-up images having different in-focus positions. 
     Other Embodiments 
     Embodiment(s) of the present invention can also be realized by a computer of a system or apparatus that reads out and executes computer executable instructions (e.g., one or more programs) recorded on a storage medium (which may also be referred to more fully as a ‘non-transitory computer-readable storage medium’) to perform the functions of one or more of the above-described embodiment(s) and/or that includes one or more circuits (e.g., application specific integrated circuit (ASIC)) for performing the functions of one or more of the above-described embodiment(s), and by a method performed by the computer of the system or apparatus by, for example, reading out and executing the computer executable instructions from the storage medium to perform the functions of one or more of the above-described embodiment(s) and/or controlling the one or more circuits to perform the functions of one or more of the above-described embodiment(s). The computer may comprise one or more processors (e.g., central processing unit (CPU), micro processing unit (MPU)) and may include a network of separate computers or separate processors to read out and execute the computer executable instructions. The computer executable instructions may be provided to the computer, for example, from a network or the storage medium. The storage medium may include, for example, one or more of a hard disk, a random-access memory (RAM), a read only memory (ROM), a storage of distributed computing systems, an optical disk (such as a compact disc (CD), digital versatile disc (DVD), or Blu-ray Disc (BD)™), a flash memory device, a memory card, and the like. 
     While the present invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions. 
     This application claims the benefit of Japanese Patent Application No. 2018-142905, filed Jul. 30, 2018, which is hereby incorporated by reference herein in its entirety.