24 September 2007 Color component cross-talk pixel SNR correction method for color imagers
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A simple multi-channel imager restoration method is presented in this paper. A method is developed to correct channel dependent cross-talk of a Bayer color filter array sensor with signal-dependent additive noise. We develop separate cost functions (weakened optimization) for each color channel-to-color channel component. Regularization is applied to each color component, instead of the standard per color channel basis. This separation of color components allows us to calculate regularization parameters that take advantage of the differing magnitudes of each color component cross-talk blurring. Due to a large variation in the amount of blurring for each color component, this separation can result in an improved trade-off between inverse filtering and noise smoothing. The restoration solution has its regularization parameters determined by maximizing the developed local pixel SNR estimations (HVS detection constraint). Local pixel adaptivity is applied. The total error in the corrected signal estimate (from bias error and amplified noise variance) is used in the local pixel SNR estimates. Sensor characterization a priori information is utilized. The method is geared towards implementation into the on-chip digital logic of low-cost CMOS sensors. Performance data of the proposed correction method is presented using color images captured from low cost embedded imaging CMOS sensors.
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Brent McCleary, "Color component cross-talk pixel SNR correction method for color imagers", Proc. SPIE 6696, Applications of Digital Image Processing XXX, 669620 (24 September 2007); doi: 10.1117/12.734695; https://doi.org/10.1117/12.734695

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