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To remove signal-dependent noise of a digital color camera, we propose a new denoising method with our hard color-shrinkage in the tight-frame grouplet transform domain. The classic hard-shrinkage works well for monochrome-image denoising. To utilize inter-channel color dependence, a noisy image undergoes the color transformation from the RGB to the luminance-and-chrominance color space, and the luminance...
To remove signal-dependent noise of a digital color camera, we present a new soft color-shrinkage scheme for color-image denoising in a wavelet transform domain. The classic soft-shrinkage scheme works well for monochrome-image denoising; to utilize inter-channel color cross-correlations, a noisy image undergoes the color-transformation from the RGB to the luminance-and-chrominance color space, and...
This paper extends the BV-L1 variational nonlinear image-decomposition approach, useful for image processing, to a genuine color-image decomposition approach. For utilizing inter-channel color cross-correlations, we introduce TV norms of color differences and TV norms of color sums into the BV-L1 energy functionals to be minimized, and then derive denoising-type decomposition-algorithm with an over-complete...
This paper presents a new image-processing (IP) pipeline adopting an image-processing approach via nonlinear image-decomposition, for a digital color camera. This new IP pipeline is composed of four stages. At the first stage, with the multiplicative BV-G image-decomposition method, each primary color channel of observed raw color data mosaicked with the Bayer color filter array is decomposed as a...
By replacing the total-variation (TV) norm in the TV variational denoising model by the Besov norm defined with the orthonormal wavelet coefficients of an image, the TV variational model is converted into the LI variational model in the wavelet domain, and its solution is the classical wavelet shrinkage. The wavelet shrinkage denoising scheme works well for monochrome images; but its direct application...
To remove signal-dependent noise of a digital camera, we present a denoising approach via nonlinear image-decomposition. In the approach, at the first decomposition stage, multiplicative image-decomposition is performed, and a noisy image is represented as a product of its two components so that its structural component corresponding to a cartoon image approximation may not be corrupted by the noise...
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