Color image denoising using wavelets and minimum cut analysis

Wavelet thresholding has proven to be an efficient edge-preserving denoising method for grayscale images, especially when it exploits the interscale correlations of wavelet coefficients. Intrascale correlations can further improve the denoising performance, but the gain for grayscale images is generally small. In this letter, we demonstrate that the gain can become substantial in color image denoising, especially for smooth image color-difference components. We then propose a new denoising method, based on the minimum cut algorithm, to exploit both the interscale and intrascale correlations of wavelet coefficients. The proposed method achieves up to 5-dB gain in peak signal-to-noise ratio for color-difference images and leads to fewer visual color artifacts.