IEEE Trans Image Process
July 2018
Image deconvolution is an ill-posed problem that usually requires prior knowledge for regularizing the feasible solutions. In literature, iterative methods estimate an intrinsic image, minimizing a cost function regularized by specific prior information. However, it is difficult to directly minimize the constrained cost function, if a nondifferentiable regularization (e.
View Article and Find Full Text PDFRecently, several red-green-blue-white (RGBW) color filter arrays (CFAs), which include highly sensitive W pixels, have been proposed. However, RGBW CFA patterns suffer from spatial resolution degradation owing to the sensor composition having more color components than the Bayer CFA pattern. RGBW CFA demosaicing methods reconstruct resolution using the correlation between white (W) pixels and pixels of other colors, which does not improve the red-green-blue (RGB) channel sensitivity to the W channel level.
View Article and Find Full Text PDFIn this paper, we propose a green (G)-channel restoration for a red-white-blue (RWB) color filter array (CFA) image sensor using the dual sampling technique. By using white (W) pixels instead of G pixels, the RWB CFA provides high-sensitivity imaging and an improved signal-to-noise ratio compared to the Bayer CFA. However, owing to this high sensitivity, the W pixel values become rapidly over-saturated before the red-blue (RB) pixel values reach the appropriate levels.
View Article and Find Full Text PDFJ Opt Soc Am A Opt Image Sci Vis
June 2016
In this paper, an algorithm is proposed to improve contrast and saturation without color degradation. The local histogram equalization (HE) method offers better performance than the global HE method, whereas the local HE method sometimes produces undesirable results due to the block-based processing. The proposed contrast-enhancement (CE) algorithm reflects the characteristics of the global HE method in the local HE method to avoid the artifacts, while global and local contrasts are enhanced.
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