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A Bayesian two-color image demosaicer and method for processing a digital color image to demosaic the image in such a way as to reduce image artifacts. The method and system are an improvement on and an enhancement to previous demosaicing techniques. A preliminary demosaicing pass is performed on th

A Bayesian two-color image demosaicer and method for processing a digital color image to demosaic the image in such a way as to reduce image artifacts. The method and system are an improvement on and an enhancement to previous demosaicing techniques. A preliminary demosaicing pass is performed on the image to assign each pixel a fully specified RGB triple color value. The final color value of pixel in the processed image is restricted to be a linear combination of two colors. Fully-specified RGB triple color values for each pixel in an image used to find two clusters represented favored two colors. The amount of contribution from these favored two colors on the final color value then is determined. The method and system also can process multiple images to improve the demosaicing results. When using multiple images, sampling can be performed at a finer resolution, known as super resolution.

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What is claimed is: 1. A method for processing a digital color image, comprising: using a general-purpose computing device having a processor to perform the following: obtaining fully-specified RGB triple color values for each pixel in the digital color image; grouping into two clusters the pixel c

What is claimed is: 1. A method for processing a digital color image, comprising: using a general-purpose computing device having a processor to perform the following: obtaining fully-specified RGB triple color values for each pixel in the digital color image; grouping into two clusters the pixel color values for pixels in a processing region around a selected pixel in the digital color image; finding a mean of each of the two clusters to generate a first favored color value corresponding to a first mean for a first cluster and a second favored color value corresponding to a second mean for a second cluster; defining a fractional blended value that specifies how much contribution the first favored color value and the second favored color value gives to a final color value; determining a maximum fractional blended value for the selected pixel defined as a blend of the first favored color value and the second favored color value that maximizes a probability of the fractional blended value given each of the pixel color values in the processing region; and using the maximum fractional blended value and the first favored color value and the second favored color value to obtain the final color value for the selected pixel in the digital color image to perform demosaicing of the digital color image to obtain an enhanced digital color image having reduced image artifacts. 2. The method of claim 1, further comprising using a preliminary pass demosaicing technique to obtain the fully-specified RGB triple color values for each pixel. 3. The method of claim 2, further comprising using a high-quality linear interpolation demosaicing technique to obtain the fully-specified RGB triple color values for each pixel. 4. The method of claim 1, further comprising defining the processing region in the digital color image as centered at a the selected pixel. 5. The method of claim 1, further comprising grouping color values for pixels in the processing region into the two clusters using a clustering technique. 6. The method of claim 5, wherein the clustering technique is a k-means clustering technique. 7. The method of claim 5, further comprising using an outlier rejection technique with the clustering technique to improve clustering results. 8. A computer-readable storage medium having stored and encoded thereon computer-executable instructions for processing a digital color image having an associated Bayer color filter, comprising: performing a preliminary demosaicing pass on the digital color image to obtain fully-specified RGB color values for each pixel in the digital color image using samples obtained from the Bayer color filter; selecting a pixel from the digital color image for processing to obtain a selected pixel; grouping into two clusters the fully-specified RGB color values for pixels in a processing region around the selected pixel; finding a mean of each of the two clusters to generate a first favored color value corresponding to a first mean for a first cluster and a second favored color value corresponding to a second mean for a second cluster; defining a fractional blended value that specifies how much contribution the first favored color value and the second favored color value gives to a final color value; determining a maximum fractional blended value for the selected pixel defined as a blend of the first favored color value and the second favored color value that maximizes a probability of the fractional blended value given each of the pixel color values in the processing region; using the maximum fractional blended value and the first favored color value and the second favored color value to obtain the final color value for the selected pixel to perform demosaicing of the digital color image; and repeating the selecting, grouping, finding, defining, determining, and using process actions set forth above for each pixel in the digital color image such that artifacts in the digital color image are reduced. 9. The computer-readable storage medium of claim 8, further comprising using a high-quality linear interpolation technique during the preliminary demosaicing pass. 10. The computer-readable storage medium of claim 8, further comprising: centering the processing region around the selected pixel; clustering the fully-specified RGB color values from pixels in the processing region into two clusters using a k-means clustering technique having outlier rejection, wherein the first favored color value and the second favored color value each have RGB color values. 11. The computer-readable storage medium of claim 10, further comprising: computing the fractional blended value for the selected pixel using sample color values from the Bayer color filter for pixels in the processing region. 12. A computer-implemented process for demosaicing a digital color image to reduce artifacts in the digital color image, comprising: using the computer having a processor to perform the following: performing high-quality linear interpolation demosaicing on the digital color image to obtain RGB triple color values for each pixel in the digital color image; selecting a pixel in the digital color image to process and designating this pixel as a processed pixel; defining a processing region centered at the processed pixel having a 5×5 pixel area; clustering RGB color values of pixels in the processing region into two clusters using a clustering technique, finding a mean of each of the two clusters to generate a first favored color value corresponding to a first mean for a first cluster and a second favored color value corresponding to a second mean for a second cluster; defining a fractional blended value that specifies how much contribution the first favored color value and the second favored color value gives to a final color value; determining a maximum fractional blended value for the processed pixel defined as a blend of the first favored color value and the second favored color value that maximizes a probability of the fractional blended value given each of the pixel color values in the processing region; and using the maximum fractional blended value and the first favored color value and the second favored color value to obtain the final color value for the processed pixel in the digital color to perform demosaicing of the digital color image and obtain a demosaiced version of the digital color image having reduced image artifacts. 13. The computer-implemented process as set forth in claim 12, further comprising computing the maximum fractional blended value, {circumflex over (α)}, by maximizing the probability of the fractional blended value, α, given by an equation: α ^ = arg ⁢ ⁢ max α ⁢ P ⁡ ( α | S , J _ , K _ ) , wherein Jis the first favored color value and Kis the second favored color value for the processed pixel, and S is a set of samples of each pixel in the processing region. 14. The computer-implemented process as set forth in claim 13, further comprising computing the final color value, C, for the processed pixel using an equation: C=(1−{circumflex over (α)}) J+{circumflex over (α)} K.