Abstract:
A system and method for confirming the accuracy of an image registration process is provided. The method includes: receiving a first image that depicts a scene area; defining a comparison area within a second image that includes the scene area; obtaining a registration model that registers the first image to the second predefined image; constructing a third image from the first image and the comparison area of the second image based on the registration model; and comparing the third image to the second image.

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation-in-part of U.S. patent application Ser. No. 10/817,476 filed on Apr. 2, 2004 now U.S. Pat. No. 7,751,651. The disclosure of the above application is incorporated herein by reference. 
    
    
     FIELD 
     The present disclosure relates to methods and systems for validating and verifying an image registration process between images of varying perspectives and geometry. 
     BACKGROUND 
     The statements in this section merely provide background information related to the present disclosure and may not constitute prior art. 
     Modern military aircraft require a capability to target precision-guided weapons. One method to do this is to use sensor images obtained by sensors carried on the aircraft. However, making an on-board sensor highly accurate so that targets can be located within a ground coordinate system with sufficient accuracy is difficult and expensive. These problems can be overcome by registering the sensor image with a predefined, geographically aligned image obtained from a reference image database. When image registration is done with sufficient accuracy, the geographic alignment of the reference image can be applied to the sensor image, to thus obtain sufficient geographic accuracy for target points selected from the sensor image. 
     As can be appreciated, image registration can be applicable to various systems employing image recognition. In some instances additional confirmation of the validity and accuracy of the registration process may be required. Such is the case with weapon targeting systems as discussed above or with aircraft navigation systems. Such may also be the case with automated inspection systems where errors in the registration process could cause substantial damage to operations or to system components. Systems employing a manual registration process may also suffer unseen errors, and could similarly benefit from a method to confirm the validity and accuracy of the registration process. 
     Registration quality confirmation has conventionally been achieved by statistical measures applied to control points, identified and measured in the two images. The statistical measures are most commonly performed for manual registration. Measurement of such control point sets can be tedious. Interpretation of the results, while statistically useful, is still a statistical process and not necessarily an indication of validity or accuracy at arbitrary points in the images. In addition, confirming the quality of the registration process can be difficult due to the difference in visual appearance of the two images. For example, the two images may be from different sensors, or be from a similar sensor but at a different time, or even be from the same sensor but from a different point of view. In each instance, the differences in appearance are enough to lower the certainty or accuracy of any registration attempt. 
     SUMMARY 
     Accordingly, a system and method of confirming the accuracy of an image registration process is provided. One implementation of the method includes receiving a first image that depicts a scene area; defining a comparison area within a second image that includes the scene area; obtaining a registration model that registers the first image to the second predefined image; constructing a third image from the first image and the comparison area of the second image based on the registration model; and comparing the third image to the second image. 
     In other features, an image registration confirmation system is provided. In one embodiment, the system includes a registration module that generates a registration model by registering a first image to a second predefined image. A validation module generates a third image based on data from the first image and based on the registration model. A comparison module compares the third image with the second predefined image to confirm the accuracy of the registration model. 
     In still other embodiments, a system for confirming the registration of a sensor image and a reference image is provided. One embodiment involves using a sensor that generates a sensor image of a scene area. A reference image datastore stores predefined reference images wherein at least one reference image includes the scene area. A registration confirmation module registers the sensor image to the reference image including the scene area and confirms the accuracy of the registration by projecting a perspective of the sensor image to a perspective of the reference image and comparing the projected sensor image to the reference image. 
     Further areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way. 
         FIG. 1  is a representation of a mobile platform, i.e., an aircraft, having an image sensor that is directed along a line of sight that intersects with a geographic location. 
         FIG. 2  is a dataflow diagram illustrating an embodiment of an image registration quality confirmation and improvement system. 
         FIG. 3  is a block diagram illustrating the relationships between images produced by the image registration quality confirmation and improvement system. 
         FIG. 4  is a flowchart illustrating an embodiment of an image registration quality confirmation and improvement method. 
         FIG. 5  is a flowchart illustrating an embodiment of a validation image construction method as performed by the image registration quality confirmation and improvement method. 
         FIG. 6  is a block diagram illustrating the pixel-to-pixel relationship used to construct a validation image. 
     
    
    
     DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS 
     The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features. 
     As can be appreciated, the image registration quality confirmation and improvement systems and methods of the present disclosure are applicable to various systems employing image recognition. Such systems may include, but are not limited to, targeting systems, navigation systems, and inspection systems. For exemplary purposes, the disclosure will be discussed in the context of a targeting system for a mobile platform which, in this example, is an aircraft  10 .  FIG. 1  shows a representation of the aircraft  10  that is equipped with a forward-looking sensor  20  (also shown in  FIG. 2 ) such as a forward-looking infrared (FLIR) sensor or a synthetic aperture radar (SAR) sensor. The figure depicts the aircraft sensor  20  of  FIG. 2  having a line of sight  12  that is directed to a geographic area  14  and intersects with the terrain of the geographic area  14  at a particular point  16 . Known sensors of this type are capable of sensing the contours of the land and/or objects within predefined boundaries of the geographic area or location  14  represented by the perimeter edge image boundary  18  shown in  FIG. 1 . 
     The sensor  20  ( FIG. 2 ) provides signals to the electronics of the aircraft  10  that produce a visual display (not shown) from a recorded pixel array (not shown) of the sensed image of the scene area  14  around the line of sight  12  within the perimeter image boundary  18 . This visual display and the recorded pixel array form a perspective image that depicts the land and objects in the scene area  14  around the point  16  being viewed by the sensor  20  ( FIG. 2 ). Each element of the recorded pixel array corresponds to a pixel (picture element) of the image. The electronics of the aircraft  10  include a registration system that registers the sensor image to a predefined reference image corresponding to the scene area  14 . The electronics of the aircraft  10  further include an image registration quality confirmation and improvement system as described hereinafter. 
     The image registration quality confirmation and improvement systems and methods of the present disclosure provide a means to validate and verify accuracy of an image registration process. Generally speaking, the image registration confirmation and improvement process employs a reference image or design model (hereinafter commonly referred to as a reference image) of the area including a scene. For example, the reference image can be an overhead or an orthographic image of the area, with precisely known geometry, and a precisely aligned elevation matrix for that area. A sub-image is extracted from the reference image and elevation matrix, using a registration model (i.e., camera model) or other perspective information. The sub-image will include the same scene area as depicted in a second image, for example an image received from a sensor (hereinafter referred to as a sensor image). The precise knowledge of the perspective and/or registration model and the geometric model of the scene area is used to prepare a validation image. The validation image includes data from the sensor image projected to coordinates of the sub-image so as to place the sensor image in the same perspective as the reference image. The validation image is then compared with the reference image. Additionally or alternatively, the registration model can be improved by adjusting the parameters of the model. The adjustments can be made based on differences found between the two images while observing the comparison. 
     With reference to  FIG. 2 , an exemplary embodiment of an image registration quality confirmation and improvement system  22  is shown. The system  22  includes one or more modules and one or more data storage devices. As used herein, the term “module” refers to at least one of an application specific integrated circuit (ASIC), an electronic circuit, a processor (shared, dedicated, or group) and/or memory that executes one or more software or firmware programs, a combinational logic circuit, and/or other suitable components that provide the described functionality. The one or more data storage devices can be at least one of Random Access Memory (RAM), Read Only Memory (ROM), a cache, a stack, or the like which may temporarily or permanently store electronic data. 
     The system  22  is shown to communicate with the sensor  20 . The system  22  receives and processes data from the sensor  20  that makes up the sensor image  24 . The system  22  includes one or more modules operable to perform image registration quality confirmation and improvement based on the sensor image  24 . As can be appreciated, various embodiments of the system  22  may include any number of modules and sub-modules. The modules shown in  FIG. 2  may be combined and/or further partitioned to similarly perform quality confirmation and improvement for image registration. In the embodiment of  FIG. 2 , a registration confirmation module  25  includes a registration module  26 , a validation module  28 , a comparison module  30 , and an update module  32 . 
     The registration module  26  receives as an input the sensor image  24 . The registration module  26  retrieves a reference image  34  from a reference image datastore  36 . The datastore  36  may include a plethora of predefined data for each pixel or coordinate of a geographic area. The reference image  34  is a subset of this pixel data that corresponds to the scene area  14  discovered by the sensor  20 . The registration module  26  may also retrieve an elevation matrix  38  that aligns with the reference image  34  from an elevation matrix datastore  40 . 
     The registration module  26  retrieves and matches the reference image  34  and the corresponding elevation matrix  38  to the sensor image  24  based on image registration methods. In one embodiment, the registration module  26  matches the reference image  34  to the sensor image  24  based on the automatic image registration methods as described in U.S. patent application Ser. No. 10/817,476 and incorporated herein by reference. The registration module  26  generates a registration model  42  that depicts the matching relationship between the sensor image  24  and the reference image  34 . As can be appreciated, the registration model  42  can be a two-dimensional or a three-dimensional model. The dimensions of the registration model  42  can depend on whether the registration method employed includes data from the elevation matrix  38  in the registration model  42 . As illustrated in  FIG. 2 , the registration model  42  in this example is two-dimensional and the elevation matrix  38  is provided as a separate data entity. 
     The validation module  28  receives as input the sensor image  24 , the registration model  42 , and the elevation matrix  38 . Based on the inputs  24 ,  42 , and  38 , the validation module  28  generates a validation image  44 . More particularly, a validation image storage is defined to hold the validation image  44 . The storage includes a size and a shape to match the size and shape of the reference image  34  or a sub-image of the reference image  34  that corresponds to the scene area  14 . The size and the shape are established through the registration model  42 . The registration model  42  provides a pixel-to-pixel correspondence between the sensor image  24  and the reference image  34 . Using this correspondence, pixel locations of the sensor image  24  are projected to the validation image  44 . Data from the sensor image  24  is used to populate the data of the validation image  44 . In various embodiments, elevation data from the elevation matrix  38  or the registration model  42  is used to populate the data of the validation image  44 . Methods and systems for constructing the validation image will be discussed in more detail below. 
     The comparison module  30  receives as input the validation image  44  and the reference image  34 . The comparison module  30  provides a means for performing a comparison between the validation image  44  and the reference image  34 . In various embodiments, the two images  34 ,  44  can be automatically compared based on various automatic data comparison methods. In various other embodiments, the comparison module  30  displays both images on a display  46  via image display data  48 . The images  34 ,  44  can be visually compared by an operator viewing the display  46 . Visual display methods may include, but are not limited to, an alternating display method, an overlay method, and a wiper bar method. 
     More particularly, the alternating or flicker display method provides an alternating display of the two images  34 ,  44  with automatic or operator controlled switching between the two images  34 ,  44 . This allows the operator to perceive common, well-registered features as stationary over time. Mis-registered or non-represented features are perceived as “jumping” over time. The overlay method overlays the two images  34 ,  44  with a top one of the two images  34 ,  44  being partially transparent. This allows the bottom image to also be seen. The operator visually perceives both images  34 ,  44  simultaneously. Mis-registered features appear as “doubled” or blurred. The “wiper bar” method provides a bar that slides across the display  46 . The two images  34 ,  44  appear on opposite sides of the bar. Mis-registered features appear to “jump” or to “break” and rejoin as the bar passes across the display  46 . 
     Based on the comparison, the validation image  44  can be adjusted either manually by input (not shown) received from the operator or automatically using adjustment methods. The adjustments to the validation image  44  are stored as adjustment data  50 . The update module  32  receives as input the adjustment data  50 . The update module  32  processes the adjustment data  50  based on the method used to perform the adjustment. Such methods may include, but are not limited to, shifting, translating, and rotating. The update data  52  is generated based on the relationship between the registration model  42  and the validation image  44 . The registration module  26  then receives the update data  52  and updates the registration model  42  accordingly. 
     With reference to  FIG. 3 , a block diagram illustrates the relationships between the images produced by the image registration quality confirmation and improvement system  22  of  FIG. 2 . Initially, the sensor image  24  of the scene area  14  is obtained. The sensor image  24  is registered to a sub-image  33  of the reference image  34  including the scene area  14 . The reference image  34  has an accurately known relationship to a scene coordinate system (not shown). This provides the sensor image  24  with an accurately known relationship to the same scene coordinate system. The relationship between the sensor image  24  and the scene coordinate system of the reference image  34  may include some small error due to residual error in registering the sensor image  24  to the sub-image  33  of the reference image  34 . 
     The elevation matrix  38  giving surface heights of the scene area  14  is associated with the scene area coordinate system of the reference image  34 . Through the scene area coordinate system a relationship between the sensor image  24  and the elevation matrix  38  can be established. Using the accurately known relationship between the sensor image  24  and the reference image  34 , and the sensor image  24  and the elevation matrix  38 , the validation image  44  that matches the geometry of the reference image  34  while containing the image content of the sensor image  24  can be produced. The validation image  44  can then be compared to the sub-image  33  of the reference image  34  or to the reference image  34 , to confirm validity of the image registration. This operation also verifies the accuracy in the reference image  34  of the locations of features seen in only the sensor image  24 , or seen in both the sensor and reference images  24 ,  34 . As shown in  FIG. 3 , the scene area  14  in the validation image  44  is misplaced due to the registration error. The validation image  44  can then be manually or automatically adjusted in comparison to the reference image  34 , to correct residual offset error in the known relationship between the sensor image  24  and the scene coordinate system, effecting an improvement in the image registration. 
     Referring now to  FIG. 4 , a flowchart illustrates an exemplary implementation of an image registration quality confirmation and improvement method  100 . As can be appreciated, the operation of the image registration quality confirmation and improvement method  100  can be executed in varying order and therefore is not limited strictly to the sequential execution as illustrated in  FIG. 4 . The method may begin at operation  110 . A sub-image  33  is defined at operation  120  to encompass sufficient area within the reference image  34  to include a majority or all of the scene area  14  depicted in the sensor image  24 . The sub-image  33  may be defined to match a rectangle of pixels in the reference image  34  or a rectangle of scene area coordinates. The sub-image  33  may be any geometric shape. A registration model that associates coordinate or pixel locations in the sensor image  24  with coordinate or pixel locations in the scene area  14  of the reference image  34  is obtained at operation  130 . This registration model may be one used in establishing the sensor image registration to the scene area coordinate system (i.e. registration model), or it might be newly defined, based on knowledge of the accurately known relationship between the sensor image  24  and the scene area coordinate system. 
     Once the comparison area is defined at operation  120  and the registration model is obtained at operation  130 , the validation image  44  is constructed at operation  140 . Operation of the validation image construction method will be discussed in more detail in the context of  FIGS. 5 and 6 . At operation  150 , the validation image  44  is compared to the reference image  34 . If differences exist between the two images  34 ,  44  at operation  160 , the validation image  44  is adjusted either manually and/or automatically at operation  170  and the registration model is updated from data obtained during the adjustment process at operation  180 . Otherwise, if no differences exist, the method proceeds to the end at operation  190 . As can be appreciated, the construction, comparison, adjustment, and update operations can be iteratively performed until an operator is satisfied with the output of the comparison or there exists no differences between the two images (as shown in  FIG. 4 ). 
     With reference to  FIGS. 5 and 6 ,  FIG. 5  includes a flowchart that illustrates an exemplary implementation of a validation image construction method  140 . As can be appreciated, operation of the validation image construction method  140  can be executed in varying order and therefore is not limited strictly to the sequential execution as illustrated in  FIG. 5 .  FIG. 6  illustrates an exemplary coordinate-to-coordinate or pixel-to-pixel relationship used to construct the validation image  44 . In  FIG. 5 , the method may begin at  200 . Coordinates in the sensor image  24  are mapped to coordinates in the reference image  34  using the one-to-one relationship established by the registration model at operation  210 . A new validation image  44  is generated including the same coordinates as the reference image at operation  220 . For each coordinate or pixel  60  in the validation image  44 , the data for the coordinate or pixel  60  is updated with the corresponding data from the coordinate or pixel  62  of the sensor image  24  at operation  230  and  240 . As can be appreciated, the order of traversing through each coordinate or pixel  60  at operation  230  can be done on a column by column basis (not shown) or a row by row basis (as shown in  FIG. 6 ) of the validation image  44 . Once the data for each coordinate or pixel  60  of the validation image  44  is updated at operation  230 , the method may end at operation  250 . 
     As can be appreciated, various other relationships and methods may be used to construct the validation image. In one other embodiment, the coordinate-to-coordinate or pixel-to-pixel relationship and method used to construct the validation image  44  is described in U.S. patent application Ser. No. 11/174,036, which is incorporated herein by reference. 
     While specific examples have been described in the specification and illustrated in the drawings, it will be understood by those of ordinary skill in the art that various changes may be made and equivalents may be substituted for elements thereof without departing from the scope of the present disclosure as defined in the claims. Furthermore, the mixing and matching of features, elements and/or functions between various examples is expressly contemplated herein so that one of ordinary skill in the art would appreciate from this disclosure that features, elements and/or functions of one example may be incorporated into another example as appropriate, unless described otherwise, above. Moreover, many modifications can be made to adapt a particular situation or material to the teachings of the present disclosure without departing from the essential scope thereof. Therefore, it is intended that the present disclosure not be limited to the particular examples illustrated by the drawings and described in the specification as the best mode presently contemplated for carrying out this disclosure, but that the scope of the present disclosure will include any embodiments falling within the foregoing description and the appended claims.