CROSS REFERENCE TO RELATED APPLICATIONS 
       [0001]    Reference is made to commonly assigned U.S. patent application Ser. No. 11/341,206, filed Jan. 27, 2006 (U.S. Patent Application Publication 2007/0024934) by James E. Adams, Jr. et al, entitled “Interpolation of Panchromatic and Color Pixels”, and U.S. patent application Ser. No. 11/564,451 filed Nov. 29, 2006 by James E. Adams, Jr. et al, entitled “Providing a Desired Resolution Color Image” the disclosures of which are incorporated herein. 
     
    
     FIELD OF THE INVENTION 
       [0002]    The present invention relates to forming a color image having a desired pixel aspect ratio from a panchromatic image and a color image having a different pixel aspect ratio. 
       BACKGROUND OF THE INVENTION 
       [0003]    Video cameras and digital still cameras generally employ a single image sensor with a color filter array to record a scene. This approach begins with a sparsely populated single-channel image in which the color information is encoded by the color filter array pattern. Subsequent interpolation of the neighboring pixel values permits the reconstruction of a complete three-channel, full-color image. A generally understood assumption is that this full-color image is composed of pixels values sampled on a square pixel lattice, i.e., the image pixels are square. This is important for the vast majority of image display and printing devices use square pixels for subsequent image rendering. However, requiring square pixels in the full-color image does not require the single image sensor to use square pixels. Sensors using rectangular (non-square) pixels are well known in the art. The general practice of producing a square pixel image from a rectangular pixel capture is to produce a full-color image with rectangular pixels and then, as a final step, transform the full-color image into one with square pixels. This approach is exemplified by U.S. Pat. No. 5,778,106 (Juenger et al.) See  FIG. 2 . A digital camera  200  equipped with a single sensor of rectangular pixels produces an RGB CFA image  202 . A CFA interpolation block  204  produces a full-color image  206  from the RGB CFA image  202 . A pixel aspect ratio correction block  208  produces a pixel aspect ratio corrected full-color image  210  from the full-color image  206 . In this example, it can be seen that an extra operation (block  208 ) is required in the image processing chain in order to produce an image with square pixels (block  210 ) from an initial image with non-square pixels (block  202 ). A better solution would be to incorporate the pixel aspect ratio correction block  208  directly into the CFA interpolation block  204 . A related example of this approach is taught in U.S. Pat. No. 7,092,020 (Yoshikawa). See  FIG. 3 . A digital camera  212  (equipped with a single sensor of square pixels) produces an RGB CFA image  214 . A CFA interpolation and resizing block  216  produces a resized full-color image  218  from the RGB CFA image  214  by directly computing a digitally zoomed (enlarged) full-color image without dividing the operation into two separate steps (interpolation then resizing) or producing a corresponding intermediate image. 
         [0004]    Under low-light imaging situations, it is advantageous to have one or more of the pixels in the color filter array unfiltered, i.e. white or panchromatic in spectral sensitivity. These panchromatic pixels have the highest light sensitivity capability of the capture system. Employing panchromatic pixels represents a tradeoff in the capture system between light sensitivity and color spatial resolution. To this end, many four-color color filter array systems have been described. U.S. Pat. No. 6,529,239 (Dyck et al.) teaches a green-cyan-yellow-white pattern that is arranged as a 2×2 block that is tessellated over the surface of the sensor. U.S. Pat. No. 6,757,012 (Hubina et al.) discloses both a red-green-blue-white pattern and a yellow-cyan-magenta-white pattern. In both cases, the colors are arranged in a 2×2 block that is tessellated over the surface of the imager. The difficulty with such systems is that only one-quarter of the pixels in the color filter array have highest light sensitivity, thus limiting the overall low-light performance of the capture device. 
         [0005]    To address the need of having more pixels with highest light sensitivity in the color filter array, U.S. Patent Application Publication No. 2003/0210332 (Frame) describes a pixel array with most of the pixels being unfiltered. Relatively few pixels are devoted to capturing color information from the scene producing a system with low color spatial resolution capability. Additionally, Frame teaches using simple linear interpolation techniques that are not responsive to or protective of high frequency color spatial details in the image. 
       SUMMARY OF THE INVENTION 
       [0006]    It is an object of the present invention to produce a digital color image having the desired pixel aspect ratio from a digital image having panchromatic and color pixels with a different pixel aspect ratio. 
         [0007]    This object is achieved by a method of forming an enhanced digital full-color image having a first pixel aspect ratio, comprising: 
         [0008]    (a) capturing an image using an image sensor having panchromatic pixels and color pixels corresponding to at least two color photoresponses wherein color and panchromatic pixels each have a second pixel aspect ratio different from the first pixel aspect ratio; 
         [0009]    (b) providing from the captured image a digital high-resolution panchromatic image and changing the aspect ratio of the panchromatic pixel values from the second pixel aspect ratio to the first pixel aspect ratio to produce a digital aspect corrected high-resolution panchromatic image; 
         [0010]    (c) providing from the captured image a digital low-resolution color difference color filter array image; 
         [0011]    (d) providing a digital aspect corrected high-resolution color difference image from the low-resolution color difference color filter array image; and 
         [0012]    (e) using the aspect corrected high-resolution panchromatic image and an aspect corrected high-resolution color difference image to produce the enhanced digital full-color image. 
         [0013]    It is a feature of the present invention that images can be captured under low-light conditions with a sensor having panchromatic and color pixels with a first pixel aspect ratio and processing produces the desired pixel aspect ration in a digital color image produced from the panchromatic and colored pixels. 
         [0014]    The present invention makes use of a color filter array with an appropriate composition of panchromatic and color pixels in order to permit the above method to provide both improved low-light sensitivity and improved color spatial resolution fidelity. The above method preserves and enhances panchromatic and color spatial details and produce a full-color, full-resolution image. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0015]      FIG. 1  is a perspective of a computer system including a digital camera for implementing the present invention; 
           [0016]      FIG. 2  is a block diagram of a prior art pixel aspect ratio correction image processing chain; 
           [0017]      FIG. 3  is a block diagram of a prior art of a combined CFA interpolation and resizing image processing chain; 
           [0018]      FIG. 4  is a block diagram of a preferred embodiment of the present invention; 
           [0019]      FIG. 5A  is a block diagram showing block  302  in  FIG. 4  in more detail; 
           [0020]      FIG. 5B  is a block diagram showing block  302  in  FIG. 4  in more detail of an alternate embodiment of the present invention; 
           [0021]      FIG. 6A  is a block diagram showing block  316  in  FIG. 4  in more detail; 
           [0022]      FIG. 6B  is a block diagram showing block  316  in  FIG. 4  in more detail of an alternate embodiment of the present invention; 
           [0023]      FIG. 6C  is a block diagram showing block  316  in  FIG. 4  in more detail of an alternate embodiment of the present invention; 
           [0024]      FIG. 6D  is a block diagram showing block  316  in  FIG. 4  in more detail of an alternate embodiment of the present invention; 
           [0025]      FIG. 6E  is a block diagram showing block  316  in  FIG. 4  in more detail of an alternate embodiment of the present invention; 
           [0026]      FIG. 6F  is a block diagram showing block  316  in  FIG. 4  in more detail of an alternate embodiment of the present invention; 
           [0027]      FIG. 7A and 7B  are regions of pixels used in block  316  in  FIG. 6A ; 
           [0028]      FIG. 8A and 8B  are regions of pixels used in block  316  in  FIG. 6C ; 
           [0029]      FIG. 9A and 9B  are regions of pixels used in block  316  in  FIG. 6D ; 
           [0030]      FIG. 10A and 10B  are regions of pixels used in block  316  in  FIG. 6E ; and 
           [0031]      FIG. 11A and 11B  are regions of pixels used in block  316  in  FIG. 6F . 
       
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
       [0032]    In the following description, a preferred embodiment of the present invention will be described in terms that would ordinarily be implemented as a software program. Those skilled in the art will readily recognize that the equivalent of such software can also be constructed in hardware. Because image manipulation algorithms and systems are well known, the present description will be directed in particular to algorithms and systems forming part of, or cooperating more directly with, the system and method in accordance with the present invention. Other aspects of such algorithms and systems, and hardware or software for producing and otherwise processing the image signals involved therewith, not specifically shown or described herein, can be selected from such systems, algorithms, components and elements known in the art. Given the system as described according to the invention in the following materials, software not specifically shown, suggested or described herein that is useful for implementation of the invention is conventional and within the ordinary skill in such arts. 
         [0033]    Still further, as used herein, the computer program can be stored in a computer readable storage medium, which can include, for example; magnetic storage media such as a magnetic disk (such as a hard drive or a floppy disk) or magnetic tape; optical storage media such as an optical disc, optical tape, or machine readable bar code; solid state electronic storage devices such as random access memory (RAM), or read only memory (ROM); or any other physical device or medium employed to store a computer program. 
         [0034]    Before describing the present invention, it facilitates understanding to note that the present invention is preferably utilized on any well-known computer system, such as a personal computer. Consequently, the computer system will not be discussed in detail herein. It is also instructive to note that the images are either directly input into the computer system (for example by a digital camera) or digitized before input into the computer system (for example by scanning an original, such as a silver halide film). 
         [0035]    Referring to  FIG. 1 , there is illustrated a computer system  110  for implementing the present invention. Although the computer system  110  is shown for the purpose of illustrating a preferred embodiment, the present invention is not limited to the computer system  110  shown, but can be used on any electronic processing system such as found in home computers, kiosks, retail or wholesale photofinishing, or any other system for the processing of digital images. The computer system  110  includes a microprocessor-based unit  112  for receiving and processing software programs and for performing other processing functions. A display  114  is electrically connected to the microprocessor-based unit  112  for displaying user-related information associated with the software, e.g., by a graphical user interface. A keyboard  116  is also connected to the microprocessor based unit  112  for permitting a user to input information to the software. As an alternative to using the keyboard  116  for input, a mouse  118  can be used for moving a selector  120  on the display  114  and for selecting an item on which the selector  120  overlays, as is well known in the art. 
         [0036]    A compact disk-read only memory (CD-ROM)  124 , which typically includes software programs, is inserted into the microprocessor based unit for providing a way of inputting the software programs and other information to the microprocessor based unit  112 . In addition, a floppy disk  126  can also include a software program, and is inserted into the microprocessor-based unit  112  for inputting the software program. The compact disk-read only memory (CD-ROM)  124  or the floppy disk  126  can alternatively be inserted into externally located disk drive unit  122  which is connected to the microprocessor-based unit  112 . Still further, the microprocessor-based unit  112  can be programmed, as is well known in the art, for storing the software program internally. The microprocessor-based unit  112  can also have a network connection  127 , such as a telephone line, to an external network, such as a local area network or the Internet. A printer  128  can also be connected to the microprocessor-based unit  112  for printing a hardcopy of the output from the computer system  110 . 
         [0037]    Images can also be displayed on the display  114  via a personal computer card (PC card)  130 , such as it was formerly known, a PCMCIA card (based on the specifications of the Personal Computer Memory Card International Association) which contains digitized images electronically embodied in the PC card  130 . The PC card  130  is ultimately inserted into the microprocessor based unit  112  for permitting visual display of the image on the display  114 . Alternatively, the PC card  130  can be inserted into an externally located PC card reader  132  connected to the microprocessor-based unit  112 . Images can also be input via the compact disk-read only memory (CD-ROM)  124 , the floppy disk  126 , or the network connection  127 . Any images stored in the PC card  130 , the floppy disk  126  or the compact disk-read only memory (CD-ROM)  124 , or input through the network connection  127 , can have been obtained from a variety of sources, such as a digital camera (not shown) or a scanner (not shown). Images can also be input directly from a digital camera  134  via a camera docking port  136  connected to the microprocessor-based unit  112  or directly from the digital camera  134  via a cable connection  138  to the microprocessor-based unit  112  or via a wireless connection  140  to the microprocessor-based unit  112 . 
         [0038]    In accordance with the invention, the algorithm can be stored in any of the storage devices heretofore mentioned and applied to images in order to interpolate sparsely populated images. 
         [0039]      FIG. 4  is a high level diagram of a preferred embodiment. The digital camera  134  ( FIG. 1 ) is responsible for creating an original digital red-green-blue-panchromatic (RGBP) color filter array (CFA) image  300 , also referred to as the digital RGBP CFA image or the RGBP CFA image. It is noted at this point that other color channel combinations, such as cyan-magenta-yellow-panchromatic, can be used in place of red-green-blue-panchromatic in the following description. The key item is the inclusion of a panchromatic channel. This image is considered to be a sparsely sampled image because each pixel in the image contains only one pixel value of red, green, blue, or panchromatic data. A panchromatic interpolation block  302  produces a high-resolution panchromatic image  304  and a low-resolution panchromatic image  306  from the RGBP CFA image  300 . At this point in the image processing chain, each color pixel location has an associated panchromatic value and either a red, green, or a blue value. The low-resolution color decimation block  310  produces a low-resolution RGB CFA image  312  from the RGBP CFA image  300 . The color differences generation block  308  produces a low-resolution color differences CFA image  314  from the low-resolution RGB CFA image  312  and the low-resolution panchromatic image  306 . The color differences CFA interpolation and resizing block  316  produces a corrected high-resolution color differences image  318  from the low-resolution color differences CFA image  314  and the low-resolution panchromatic image  306 . The pixel aspect ratio correction block  320  produces a corrected high-resolution panchromatic image  322  from the high-resolution panchromatic image  304 . Finally, the color differences and panchromatic image summation block  324  produces an enhanced full-color image  326  from the corrected high-resolution color differences image  318  and the corrected high-resolution panchromatic image  322 . 
         [0040]      FIG. 5A  is a more detailed view of block  302  ( FIG. 4 ) of the preferred embodiment. The high-resolution panchromatic interpolation block  328  produces a high-resolution panchromatic image  330  from the RGBP CFA image  300  ( FIG. 4 ). A copy of the high-resolution panchromatic image  330  becomes the high-resolution panchromatic image  304  ( FIG. 4 ). The low-resolution panchromatic decimation block  332  produces the low-resolution panchromatic image  306  ( FIG. 4 ) from the high-resolution panchromatic image  330 . 
         [0041]    In  FIG. 5A , the high-resolution panchromatic interpolation block  328  and the low-resolution panchromatic decimation block  332  can be performed in any ways known to those skilled in the art. Suitable methods are taught in above-cited, commonly-assigned U.S. Patent Application Publication No. 2007/0024934 and U.S. patent application Ser. No. 11/564,451. 
         [0042]      FIG. 5B  is a more detailed view of block  302  ( FIG. 4 ) of an alternate embodiment. The high-resolution panchromatic interpolation block  328  produces the high-resolution panchromatic image  304  ( FIG. 4 ) from the RGBP CFA image  300  ( FIG. 4 ). The low-resolution panchromatic interpolation block  334  produces the low-resolution panchromatic image  306  ( FIG. 4 ) from the RGBP CFA image  300  ( FIG. 4 ). The high-resolution panchromatic interpolation block  328  has already been discussed under  FIG. 5A . The low-resolution panchromatic interpolation block  334  differs from the high-resolution panchromatic interpolation block  328  only in that the captured panchromatic pixel values are automatically discarded after the interpolation computations in order to produce a low-resolution panchromatic image of interpolated panchromatic pixel values. 
         [0043]      FIG. 6A  is a more detailed view of block  316  ( FIG. 4 ) of the preferred embodiment. A color differences CFA interpolation block  336  produces a low-resolution color differences image  338  from the low-resolution color differences CFA image  314  ( FIG. 4 ). A high-resolution resizing block  340  produces a high-resolution color differences image  342  from the low-resolution color differences image  338 . A pixel aspect ratio correction block  344  produces the corrected high-resolution color differences image  318  ( FIG. 4 ) from the high-resolution color differences image  342 . 
         [0044]    In  FIG. 6A , the color differences CFA interpolation block  336  may be performed in any way known to those skilled in the art. Suitable methods are taught in above-cited, commonly-assigned U.S. Patent Application Publication No. 2007/0024934 and U.S. patent application Ser. No. 11/564,451. The high-resolution resizing block  340  is a standard digital image resizing (interpolation or resampling) operation with an appropriate method described also in commonly-assigned U.S. Patent Application Publication No. 2007/0024934. The pixel aspect ratio correction block  344  is also a standard digital image resizing operation with the notable feature that the horizontal scale factor differs from the vertical scale factor. As an example,  FIG. 7B  (Q 1 -Q C ) represents the pixel aspect ratio corrected version of  FIG. 7A  (P 1 -P C ). Using bilinear interpolation, the pixel aspect ratio computation would be as follows: 
         [0000]      Q 1 =P 1    
         [0000]        Q   2 =(2 P   2   +P   3 )/3 
         [0000]        Q   3 =( P   3 +2 P   4 )/3 
         [0000]        Q   4 =( P   1 +3 P   5 )/4 
         [0000]        Q   5 =(2 P   2   +P   3 +6 P   6 +3 P   7 )/12 
         [0000]        Q   6 =( P   3 +2 P   4 +3 P   7 +6 P   8 )/12 
         [0000]        Q   7 =( P   5   +(   9 )/2 
         [0000]        Q   8 =(2 P   6   +P   7 +2 P   A   +P   B )/6 
         [0000]        Q   9 =( P   7 +2 P   8   +P   8 +2 P   C )/6 
         [0000]        Q   A =(3 P   9   +P   D )/4 
         [0000]        Q   B =(6 P   A +3 P   B +2 P   E   +P   F )/12 
         [0000]        Q   C =(3 P   B +6 P   C   +P   F +2 P   G )/12 
         [0000]    It will be apparent to one skilled in the art that other methods of interpolation, such as cubic convolution interpolation, can be used in place of bilinear interpolation. 
         [0045]      FIG. 6B  is a more detailed view of block  316  ( FIG. 4 ) of an alternate embodiment. A color differences CFA interpolation block  336  produces a low-resolution color differences image  338  from the low-resolution color differences CFA image  314  ( FIG. 4 ). A pixel aspect ratio correction block  346  produces a corrected color differences image  348  from the low-resolution color differences image  338 . A high-resolution resizing block  350  produces the corrected high-resolution color differences image  318  ( FIG. 4 ) from the corrected color differences image  348 . 
         [0046]    In  FIG. 6B , the color differences CFA interpolation block  336  is as previously described under  FIG. 6A . The pixel aspect ratio correction block  346  is the same as the pixel aspect ratio correction block  344  of  FIG. 6A  except that block  346  operates on low-resolution data and block  344  operates on high-resolution data. The high-resolution resizing block  350  is the same as the high-resolution resizing block  340  except that block  350  operates on pixel aspect ratio corrected data and block  340  does not. 
         [0047]      FIG. 6C  is a more detailed view of block  316  ( FIG. 4 ) of an alternate embodiment. A color differences CFA interpolation block  336  produces a low-resolution color differences image  338  from the low-resolution color differences CFA image  314  ( FIG. 4 ). A high-resolution resizing and pixel aspect ratio correction block  352  produces the corrected high-resolution color differences image  318  ( FIG. 4 ) from the low-resolution color differences image  338 . 
         [0048]    In  FIG. 6C , the color differences CFA interpolation block  336  is as previously described under  FIG. 6A . The high-resolution resizing and pixel aspect ratio correction block  352  performs high-resolution resizing and pixel aspect ratio correction as a single operation. Block  352  is accomplished by a standard resizing operation with different scale factors for the horizontal and vertical directions. As an example,  FIG. 8B  (Q 1 -Q m ) represents the high-resolution resized and pixel aspect ratio corrected version of  FIG. 8A  (P 1 -P C ). Using bilinear interpolation, the pixel aspect ratio computation in part would be as follows: 
         [0000]      Q 1 =P 1    
         [0000]        Q   2 =( P   1 +2 P   2 )/3 
         [0000]        Q   3 =(2 P   2   +P   3 )/3 
         [0000]        Q   7 =(5 P   1 +3 P   5 )/8 
         [0000]      Q 8 =(5 P   1 +10 P   2 +3 P   5 +6 P   6 )/24 
         [0000]        Q   9 =(10 P   2 +5 P   3 +6 P   6 +3 P   7 )/24 
         [0000]        Q   D =( P   1 +3 P   5 )/4 
         [0000]        Q   E =( P   1 +2 P   2 +3 P   5 +6 P   6 )/12 
         [0000]        Q   F =(2 P   2   +P   3 +6 P   6 +3 P   7 )/6 
         [0000]        Q   J =(7 P   5   +P   9 )/8 
         [0000]        Q   K =(7 P   5 +14 P   6   +P   9 +2 P   A )/24 
         [0000]        Q   L =(14 P   6 +7 P   7 +2 P   A   +P   B )/24 
         [0000]    It will be apparent to one skilled in the art how to extend these computations to produce the other values of Q in  FIG. 8B . It will also be apparent to one skilled in the art that other methods of interpolation, such as cubic convolution interpolation, can be used in place of bilinear interpolation. 
         [0049]      FIG. 6D  is a more detailed view of block  316  ( FIG. 4 ) of an alternate embodiment. A color differences CFA interpolation and pixel aspect ratio correction block  354  produces a corrected low-resolution color differences image  356  from the low-resolution color differences CFA image  314  ( FIG. 4 ). A high-resolution resizing block  358  produces the corrected high-resolution color differences image  318  ( FIG. 4 ) from the corrected low-resolution color differences image  356 . 
         [0050]    In  FIG. 6D , the high-resolution resizing block  358  is the same as the high-resolution resizing block  340  ( FIG. 6A ) except that block  358  operates on pixel aspect ratio corrected data. The color differences CFA interpolation and pixel aspect ratio correction block  354  is a combined interpolation operation. As an example,  FIG. 9B  (Q 1 -Q C ) represents the CFA interpolated and pixel aspect ratio corrected version of  FIG. 9A  (R 1 -G C ). Note that in  FIG. 9A , each pixel value is a color difference value and not an original color value. Since pixels Q 1  and R 1  are coincident, no pixel aspect ratio correction is required for Q 1 . Therefore, only CFA interpolation is performed. Standard bilinear interpolation is employed: 
         [0051]    Q 1R =R 1    
         [0000]        Q   1G =( G   E   +G   J   +G   2   +G   5 )/4 
         [0000]        Q   1B =( B   D   +B   F   +B   L   +B   6 )/4 
         [0000]    In the case of Q 2 , both CFA interpolation and pixel aspect ratio correction are performed. Intermediate steps are shown to illustrate the determination of the final computation. 
         [0000]        Q   2R =(2 R   2   +R   3 )/3→(2( R   1   +R   3 )/2 +R   3 )/3→( R   1 +2 R   3 )/3 
         [0000]        Q   2G =(2 G   2   +G   3 )/3→(2 G   2 +( G   G   +G   2   +G   7   +G   4 )/4)/3→(9 G   2   +G   G   +G   7   +G   4 )/12 
         [0000]        Q   2B =(2 B   2   +B   3 )/3→(2( B   F   +B   6 )/2+( B   F   +B   H   +B   6   +B   8 )/4)/3→(5 B   F +5 B   6   +B   H   +B   8 )/12 
         [0000]    Therefore, the computations performed by block  354  to determine the Q 2  pixel values are: 
         [0000]        Q   2R =( R   1 +2 R   3 )/3 
         [0000]        Q   2G =(9 G   2   +G   C   +G   7   +G   4 )/12 
         [0000]        Q   2B =(5 B   F +5 B   6   +B   H   +B   8 )/12 
         [0000]    The remaining computations in the example are given below. 
         [0000]        Q   3R (2 R   3   +R   K )/3 
         [0000]        Q   3G =(9 G   4   +G   G   +G   2   +G   7 )/12 
         [0000]        Q   3B =(5 B   H +5 B   8   +B   F   +B   6 )/12 
         [0000]        Q   4R =(5 R   1 +3 R   9 )/8 
         [0000]        Q   4G =(13 G   5   +G   2   +G   E   +G   J )/16 
         [0000]        Q   4B =(7 B   1 +7 B   6   +B   D   +B   F )/16 
         [0000]        Q   5R =(10 R   3 +6 R   B +5 R   1 +3 R   9 )/24 
         [0000]        Q   5G =( G   G +15 G   2 +6 G   5   +G   4 +19 G   7 +6 G   A )/48 
         [0000]        Q   5B =(35 B   6 +7 B   8 +5 B   F   +B   H )/48 
         [0000]        Q   6R =(10 R   3 +6 R   B +5 R   K +3 R   O )/24 
         [0000]        Q   6G =( G   G   +G   2 +15 G   4 +19 G   7 +6 G   M +6 G   C )/48 
         [0000]        Q   6B =( B   F +5 B   H +7 B   6 +35 B   8 )/48 
         [0000]        Q   7R =( R   1 +3 R   9 )/4 
         [0000]        Q   7G =( G   A +5 G   5   +G   N   +G   Q )/8 
         [0000]        Q   7B =(3 B   6 +3 B   L   +B   P   +B   R )/8 
         [0000]        Q   8R =(6 R   B   +R   1 +2 R   3 +3 R   9 )/12 
         [0000]        Q   8G =(11 G   A   +G   C +2 G   2 +2 G   5 +7 G   7   +G   S )/24 
         [0000]        Q   8B =(15 B   6 +3 B   8 +5 B   R   +B   T )/24 
         [0000]        Q   9R =(6 R   B   +R   K +3 R   O +2 R   3 )/12 
         [0000]        Q   9G =( G   A +11 G   C +2 G   4 +7 G   7 +2 G   M   +G   S )/24 
         [0000]        Q   9B =(3 B   6 +15 B   8   +B   R +5 B   T )/24 
         [0000]        Q   AR =(7 R   9   +R   W )/8 
         [0000]        Q   AG =(3 G   A +3 G   5 +3 G   N +7 G   Q )/16 
         [0000]        Q   AB =(3 B   6 +3 B   L +5 B   P +5 B   R )/16 
         [0000]        Q   BR =(14 R   B +7 R   9   +R   W +2 R   Y )/24 
         [0000]        Q   BG =(29 G   A +3 G   C +3 G   7 +2 G   Q +9 G   S +2 G   X )/48 
         [0000]        Q   BB =(15 B   6 +3 B   8 +25 B   R +5 B   T )/48 
         [0000]        Q   CR =( R   a +14 R   B +7 R   O +2 R   Y )/24 
         [0000]        Q   CG =(3 G   A +29 G   C +3 G   7 +9 G   S +2 G   U +2 G   Z )/48 
         [0000]        Q   CB =(3 B   6 +15 B   8 +5 B   R +25 B   T )/48 
         [0000]    It will be apparent to one skilled in the art that other methods of interpolation, such as cubic convolution interpolation, can be used in place of bilinear interpolation. 
         [0052]      FIG. 6E  is a more detailed view of block  316  ( FIG. 4 ) of an alternate embodiment. A color differences CFA interpolation and high-resolution resizing block  360  produces a high-resolution color differences image  362  from the low-resolution color differences CFA image  314  ( FIG. 4 ). A pixel aspect ratio correction block  364  produces the corrected high-resolution color differences image  318  ( FIG. 4 ) from the high-resolution color differences image  362 . 
         [0053]    In  FIG. 6E , the pixel aspect ratio correction block  364  is the same as the pixel aspect ratio correction block  344  ( FIG. 6A ). The color differences CFA interpolation and high-resolution resizing block  360  is a combined interpolation operation. As an example,  FIG. 10B  (Q 1 -Q G ) represents the CFA interpolated and high-resolution resized version of  FIG. 10A  (R 1 -B 4 ). Note that in  FIG. 10A , each pixel value is a color difference value and not an original color value. Since pixels Q 1  and R 1  are coincident, no high-resolution resizing is required for Q 1 . Therefore, only CFA interpolation is performed. Standard bilinear interpolation is employed: 
         [0000]      Q 1R =R 1    
         [0000]        Q   1G =( G   6   +G   A   +G   2   +G   3 )/4 
         [0000]        Q   1B =( B   5   +B   7   +B   D   +B   4 )/4 
         [0000]    In the case of Q 2 , both CFA interpolation and high-resolution resizing are performed. Intermediate steps are shown to illustrate the determination of the final computation. 
         [0000]        Q   2R =( R   1   +R   2 )/2→(R 1 +( R   1   +R   B )/2)/2→(3 R   1   +R   B )/4 
         [0000]        Q   2G =( G   1   +G   2 )/2→(( G   A   +G   2   +G   6   +G   3 )/4 +G   2 )/2→(5 G   2   +G   A   +G   6   +G   3 )/8 
         [0000]        Q   2B =( B   1   +B   2 )/2→(( B   5   +B   7   +B   D   +B   4 )/4+( B   7   +B   4 )/2)/2→(3 B   4   +B   5 +3 B   7   +B   D )/8 
         [0000]    Therefore, the computations performed by block  360  to determine the Q 2  pixel values are: 
         [0000]        Q   2R =(3 R   1   +R   B )/4 
         [0000]        Q   2G =(5 G   2   +G   A   +G   6   +G   3 )/8 
         [0000]        Q   2B =(3 B   4   +B   5 +3 B   7   +B   D )/8 
         [0000]    The remaining computations in the example are given below. 
         [0000]        Q   3R =( R   1   +R   B )/2 
         [0000]      Q 3G =G 2    
         [0000]        Q   3B =( B   7   +B   4 )/2 
         [0000]        Q   4R =( R   1 +3 R   B )/4 
         [0000]        Q   4G =(3 G   2   +G   C )/4 
         [0000]        Q   4B =(3 B   4   +B   9 +3 B   7   +B   F )/8 
         [0000]        Q   5R =(3 R   1   +R   H )/4 
         [0000]        Q   5G =( G   A   +G   2 +5 G   3   +G   6 )/8 
         [0000]        Q   5B =(3 B   4   +B   5   +B   7 +3 B   D )/8 
         [0000]        Q   6R =(3 R   B +3 R   H   +R   J +9 R   1 )/16 
         [0000]        Q   6G =( G   A +6 G   2 +6 G   3   +G   6   +G   E   +G   1 )/16 
         [0000]        Q   6B =(9 B   4   +B   5 +3 B   7 +3 B   D )/16 
         [0000]        Q   7R =(3 R   B   +R   H   +R   J +3 R   1 )/8 
         [0000]        Q   7G =(5 G   2   +G   3   +G   E   +G   1 )/8 
         [0000]        Q   7B =(3 B   4   +B   7 )/4 
         [0000]        Q   8R =(9 R   B   +R   H +3 R   J +3 R   1 )/16 
         [0000]        Q   8G =( G   C +6 G   2   +G   3   +G   8 +6 G   E   +G   1 )/16 
         [0000]      Q 8B =(9 B   4 +3 B   7   +B   9 +3 B   F )/16 
         [0000]        Q   9R =( R   1   +R   H )/2 
         [0000]      Q 9G =G 3    
         [0000]        Q   9B =( B   D   +B   4 )/2 
         [0000]        Q   AR =( R   B +3 R   H   +R   J +3 R   1 )/8 
         [0000]        Q   AG =( G   2 +5 G   3   +G   E   +G   1 )/8 
         [0000]        Q   AB =(3 B   4 +B D )/4 
         [0000]        Q   BR =( R   1   +R   B   +R   H   +R   J )/4 
         [0000]        Q   BG =( G   2   +G   3   +G   E   +G   1 )/4 
         [0000]      Q BB =B 4    
         [0000]        Q   CR =(3 R   B   +R   H +3 R   J   +R   1 )/8 
         [0000]        Q   CG =( G   2   +G   3 +5 G   E   +G   1 )/8 
         [0000]        Q   CB =(3 B   4   +B   F )/4 
         [0000]        Q   DR =(3 R   H   +R   1 )/4 
         [0000]        Q   DG =( G   G +5 G   3   +G   M   +G   1 )/8 
         [0000]        Q   DB =(3 B   4 +3 B   D   +B   L   +B   N )/8 
         [0000]        Q   ER =( R   B +9 R   H +3 R   J +3 R   1 )/16 
         [0000]        Q   EG =( G   G   +G   2 +6 G   3   +G   M   +G   E +6 G   1 )/16 
         [0000]        Q   EB =(9 B   4 +3 B   D   +B   L +3 B   N )/16 
         [0000]        Q   FR =( R   B +3 R   H +3 R   J   +R   1 )/8 
         [0000]        Q   FG =( G   2   +G   3   +G   E +5 G   1 )/8 
         [0000]        Q   FB =(3 B   4   +B   N )/4 
         [0000]        Q   GR =(3 R   B +3 R   H +9 R   J   +R   1 )/16 
         [0000]        Q   GG =( G   2   +G   3   +G   K   +G   O +6 G   E +6 G   1 )/16 
         [0000]      Q GB =(9 B   4 +3 B   F +3 B   N   +B   P )/16 
         [0000]    It will be apparent to one skilled in the art that other methods of interpolation, such as cubic convolution interpolation, can be used in place of bilinear interpolation. 
         [0054]      FIG. 6F  is a more detailed view of block  316  ( FIG. 4 ) of an alternate embodiment. A color differences CFA interpolation, high-resolution resizing, and pixel aspect ratio correction block  366  produces the corrected high-resolution color differences image  318  ( FIG. 4 ) from the low-resolution color differences CFA image  314  ( FIG. 4 ). Block  366  is a combined interpolation operation. As an example,  FIG. 11B  (Q 1 -Q O ) represents the CFA interpolated, high-resolution resized, and pixel aspect ratio corrected version of  FIG. 11A  (R 1 l -G   6 ). Note that in  FIG. 11A , each pixel value is a color difference value and not an original color value. Since pixels Q 1  and R 1  are coincident, no high-resolution resizing or pixel aspect ratio correction is required for Q 1 . Therefore, only CFA interpolation is performed. Standard bilinear interpolation is employed: 
         [0000]      Q 1R =R 1    
         [0000]        Q   1G =( G   8   +G   D   +G   2   +G   4 )/4 
         [0000]        Q   1B =( B   7   +B   9   +B   G   +B   5 )/4 
         [0000]    In the case of Q 2 , CFA interpolation, high-resolution resizing, and pixel aspect ratio correction are performed. Intermediate steps are shown to illustrate the determination of the final computation. 
         [0000]      Q 2R =( R   1 +3 R   2 )/4→( R   1 +3( R   1   +R   3 )/2)/4→(5 R   1 +3 R   3 )/8 
         [0000]        Q   2G =( G   1 +3 G   2 )/4→(( G   8   +G   D   +G   4   +G   2 )/4+3 G   2 )/4→( G   D +13 G   2   +G   4   +G   8 )/16 
         [0000]        Q   2B =( B   1 +3 B   2 )/4→(( B   7   +B   9   +B   G   +B   5 )/4+(B 9   +B   5 )/2)/4→(7 B   5   +B   7 +7 B   9   +B   G )/16 
         [0000]    Therefore, the computations performed by block  360  to determine the Q 2  pixel values are: 
         [0000]        Q   2R =(5 R   1 +3 R   3 )/8 
         [0000]        Q   2G =( G   D +13 G   2   +G   4   +G   8 )/16 
         [0000]        Q   2B =(7 B   5   +B   7 +7 B   9   +B   G )/16 
         [0000]    The remaining computations in the example are given below. 
         [0000]        Q   3R =( R   1 +3 R   3 )/4 
         [0000]        Q   3G =( G   A +5 G   2   +G   6   +G   E )/8 
         [0000]        Q   3B =( B   B +3 B   5 +3 B   9   +B   H )/8 
         [0000]        Q   4R =( R   F +7 R   3 )/8 
         [0000]        Q   4G =(3 G   A +3 G   2 +3 G   6 +7 G   E )/16 
         [0000]        Q   4B =(5 B   B +3 B   5 +3 B   9 +5 B   H )/16 
         [0000]        Q   5R =( R   K +5 R   1 )/6 
         [0000]        Q   5G =( G   D   +G   2 +3 G   4   +G   8 )/6 
         [0000]        Q   5B =(2 B   5   +B   7   +B   9 +2 B   G )/6 
         [0000]        Q   6R =(5 R   K +3 R   M +25 R   1 +15 R   3 )/48 
         [0000]        Q   6G =(2 G   D +29 G   2 +9 G   4 +3 G   6 +2 G   8 +3 G   L )/48 
         [0000]        Q   6B =(14 B   5   +B   7 +7 B   9 +2 B   G )/24 
         [0000]        Q   7R =( R   K +3 R   M +5 R   1 +19 R   3 )/24 
         [0000]        Q   7G =(2 G   A +11 G   2   +G   4 +7 G   6   +G   L +2 G   E )/24 
         [0000]        Q   7B =( B   B +6 B   5 +3 B   9 +2 B   H )/12 
         [0000]      Q 8R =(5 R   F +7 R   M   +R   O +35 R   3 )/48 
         [0000]        Q   8G =(6 G   A +6 G   2 +19 G   6   +G   N +15 G   E   +G   1 )/48 
         [0000]        Q   8B =(7 B   B +9 B   5 +3 B   9 +17 B   H )/48 
         [0000]        Q   9R =( R   K +2 R   1 )/3 
         [0000]        Q   9G =( G   D   +G   2 +9 G   4   +G   8 )/12 
         [0000]        Q   9B =(5 B   5   +B   7   +B   9 +5 B   G )/12 
         [0000]        Q   AR =(5 R   K +3 R   M +10 R   1 +6 R   3 )/24 
         [0000]        Q   AG =( G   D +19 G   2 +15 G   4 +6 G   6   +G   8 +6 G   L )/48 
         [0000]        Q   AB =(35 B   5   +B   7 +7 B   9 +5 B   G )/48 
         [0000]        Q   BR =( R   K +3 R   M +2 R   1 +6 R   3 )/12 
         [0000]        Q   BG =( G   A +7 G   2 +2 G   4 +11 G   6 +2 G   L   +G   E )/24 
         [0000]        Q   BB =( B   B +15 B   5 +3 B   9 +5 B   H )/24 
         [0000]        Q   CR =(2 R   F +7 R   M   +R   O +14 R   3 )/24 
         [0000]        Q   CG =(3 G   A +3 G   2 +29 G   6 +2 G   N +9 G   E +2 G   1 )/48 
         [0000]        Q   CB =(5 B   B +15 B   5 +3 B   9 +25 B   H )/48 
         [0000]        Q   DR =( R   1   +R   K )/2 
         [0000]      Q DG =G 4    
         [0000]        Q   DB =( B   G   +B   5 )/2 
         [0000]        Q   ER =(5 R   K +3 R   M +5 R   1 +3 R   3 )/16 
         [0000]        Q   EG =(3 G   2 +7 G   4 +3 G   6 +3 G   1 )/16 
         [0000]        Q   EB =(7 B   5   +B   G )/8 
         [0000]        Q   FR =( R   K +3 R   M   +R   1 +3 R   3 )/8 
         [0000]      Q FG =( G   2   +G   4 +5 G   6   +G   1 )/8 
         [0000]        Q   FB =(3 B   5   +B   H )/4 
         [0000]        Q   GR =( R   F +7 R   M   +R   O +7 R   3 )/16 
         [0000]        Q   GG =(13 G   6   +G   N   +G   E   +G   1 )/16 
         [0000]        Q   GB =(3 B   5 +5 B   H )/8 
         [0000]        Q   HR =(2 R   K   +R   1 )/3 
         [0000]        Q   HG =(9 G   4   +G   J   +G   1   +G   Q )/12 
         [0000]        Q   HB =(5 B   5 +5 B   G   +B   P   +B   R )/12 
         [0000]        Q   1R =(10 R   K +6 R   M +5 R   1 +3 R   3 )/24 
         [0000]        Q   1G =(6 G   2 +15 G   4 +6 G   6   +G   J +19 G   L   +G   Q )/48 
         [0000]        Q   1B =(35 B   5 +5 B   G   +B   P +7 B   R )/48 
         [0000]        Q   JR =(2 R   K +6 R   M   +R   1 +3 R   3 )/12 
         [0000]        Q   JG =(2 G   2 +2 G   4 +11 G   6 +7 G   L   +G   N   +G   S )/24 
         [0000]        Q   JB =(15 B   5 +5 B   H +3 B   R   +B   T )/24 
         [0000]        Q   KR =( R   F +14 R   M +2 R   O +7 R   3 )/24 
         [0000]        Q   KG =(29 G   6 + 3   G   L +9 G   N +3 G   S +2 G   E +2 G   1 )/48 
         [0000]        Q   KB =(15 B   5 +25 B   H +3 B   R +5 B   T )/48 
         [0000]        Q   LR =(5 R   K   +R   1 )/6 
         [0000]        Q   LG =(3 G   4   +G   J   +G   L   +G   Q )/6 
         [0000]        Q   LB =(2 B   5 +2 B   G   +B   P   +B   R )/6 
         [0000]        Q   MR =(25 R   K +15 R   M +5 R   1 +3 R   3 )/48 
         [0000]        Q   MG =(3 G   2 +9 G   4 +3 G   6 +2 G   J +29 G   L +2 G   Q )/48 
         [0000]        Q   MB =(14 B   5 +2 B   G   +B   P +7 B   R )/24 
         [0000]        Q   NR =(5 R   K +15 R   M   +R   1 +3 R   3 )/24 
         [0000]      Q NG =(G 3   +G   4 +7 G   6 +11 G   1 +2 G   N +2 G   S )/24 
         [0000]        Q   NB =(6 B   S +2 B   H +3 B   R   +B   T )/12 
         [0000]        Q   OR =( R   F +35 R   M +5 R   0 +7 R   3 )/48 
         [0000]        Q   OG =(19 G   6 +6 G   L +15 G   N +6 G   S   +G   E   +G   1 )/48 
         [0000]        Q   OB =(6 B   5 +10 B   H +3 B   R +5 B   T )/24 
         [0000]    It will be apparent to one skilled in the art that other methods of interpolation, such as cubic convolution interpolation, can be used in place of bilinear interpolation. 
         [0055]    The pixel aspect ratio correction algorithms disclosed in the preferred embodiments of the present invention can be employed in a variety of user contexts and environments. Exemplary contexts and environments include, without limitation, wholesale digital photofinishing (which involves exemplary process steps or stages such as film in, digital processing, prints out), retail digital photofinishing (film in, digital processing, prints out), home printing (home scanned film or digital images, digital processing, prints out), desktop software (software that applies algorithms to digital prints to make them better—or even just to change them), digital fulfillment (digital images in—from media or over the web, digital processing, with images out—in digital form on media, digital form over the web, or printed on hard-copy prints), kiosks (digital or scanned input, digital processing, digital or scanned output), mobile devices (e.g., PDA or cell phone that can be used as a processing unit, a display unit, or a unit to give processing instructions), and as a service offered via the World Wide Web. 
         [0056]    In each case, the pixel aspect ratio correction algorithms can stand alone or can be a component of a larger system solution. Furthermore, the interfaces with the algorithm, e.g., the scanning or input, the digital processing, the display to a user (if needed), the input of user requests or processing instructions (if needed), the output, can each be on the same or different devices and physical locations, and communication between the devices and locations can be via public or private network connections, or media based communication. Where consistent with the foregoing disclosure of the present invention, the algorithms themselves can be fully automatic, can have user input (be fully or partially manual), can have user or operator review to accept/reject the result, or can be assisted by metadata (metadata that can be user supplied, supplied by a measuring device (e.g. in a camera), or determined by an algorithm). Moreover, the algorithms can interface with a variety of workflow user interface schemes. 
         [0057]    The pixel aspect ratio correction algorithms disclosed herein in accordance with the invention can have interior components that utilize various data detection and reduction techniques (e.g., face detection, eye detection, skin detection, flash detection). 
         [0058]    The invention has been described in detail with particular reference to certain preferred embodiments thereof, but it will be understood that variations and modifications can be effected within the spirit and scope of the invention. 
       Parts List  
       [0000]    
       
           110  Computer System 
           112  Microprocessor-based Unit 
           114  Display 
           116  Keyboard 
           118  Mouse 
           120  Selector on Display 
           122  Disk Drive Unit 
           124  Compact Disk—read Only Memory (CD-ROM) 
           126  Floppy Disk 
           127  Network Connection 
           128  Printer 
           130  Personal Computer Card (PC card) 
           132  PC Card Reader 
           134  Digital Camera 
           136  Camera Docking Port 
           138  Cable Connection 
           140  Wireless Connection 
           200  Digital Camera 
           202  RGB CFA Image 
           204  CFA Interpolation 
           206  Full-Color Image 
           208  Pixel Aspect Ratio Correction 
           210  Corrected Full-Color Image 
           212  Digital Camera 
           214  RGB CFA Image 
           216  CFA Interpolation and Resizing 
           218  Resized Full-Color Image 
           300  RGBP CFA Image 
           302  Panchromatic Interpolation 
           304  High-Resolution Panchromatic Image 
           306  Low-Resolution Panchromatic Image 
       
     
       Parts List Cont&#39;d 
       [0000]    
       
           308  Color Differences Generation 
           310  Low-Resolution Color Decimation 
           312  Low-Resolution RGB CFA Image 
           314  Low-Resolution Color Differences CFA Image 
           316  Color Differences CFA Interpolation and Resizing 
           318  Corrected High-Resolution Color Differences Image 
           320  Pixel Aspect Ratio Correction 
           322  Corrected High-Resolution Panchromatic Image 
           324  Color Differences and Panchromatic Image Summation 
           326  Enhanced Full-Color Image 
           328  High-Resolution Panchromatic Interpolation 
           330  High-Resolution Panchromatic Image 
           332  Low-Resolution Panchromatic Decimation 
           334  Low-Resolution Panchromatic Interpolation 
           336  Color Differences CFA Interpolation 
           338  Low-Resolution Color Differences Image 
           340  High-Resolution Resizing 
           342  High-Resolution Color Differences Image 
           344  Pixel Aspect Ratio Correction 
           346  Pixel Aspect Ratio Correction 
           348  Corrected Color Differences Image 
           350  High-Resolution Resizing 
           352  High-Resolution Resizing and Pixel Aspect Ratio Correction 
           354  Color Differences CFA Interpolation and Pixel Aspect Ratio Correction 
           356  Corrected Low-Resolution Color Differences Image 
           358  High-Resolution Resizing 
           360  Color Differences CFA Interpolation and High-Resolution Resizing 
       
     
       Parts List Cont&#39;d 
       [0000]    
       
           362  High-Resolution Color Differences Image 
           364  Pixel Aspect Ratio Correction 
           366  Color Differences CFA Interpolation, High-Resolution Resizing, and Pixel Aspect Ratio Correction
A method for forming an enhanced digital full-color image having a first pixel aspect ratio includes capturing an image using an image sensor having panchromatic pixels and color pixels corresponding to at least two color photoresponses wherein color and panchromatic pixels each have a second pixel aspect ratio different from the first pixel aspect ratio, providing from the captured image a digital high-resolution panchromatic image and changing the aspect ratio of the panchromatic pixel values from the second pixel aspect ratio to the first pixel aspect ratio to produce a digital aspect corrected high-resolution panchromatic image, providing from the captured image a digital low-resolution color difference color filter array image, providing a digital aspect corrected high-resolution color difference image from the low-resolution color difference color filter array image, and using the aspect corrected high-resolution panchromatic image and an aspect corrected high-resolution color difference image to produce the enhanced digital full-color image.