Nonlinear decomposition-and-denoising approach for removal of signal-dependent noise of a digital color camera

Abstract

In a digital camera, several factors cause signal-dependency of additive noise. Many denoising methods have been proposed, but unfortunately most of them do not work well for the actual signal-dependent noise. To solve the problem of removing the signal-dependent noise of a digital camera, this paper presents a denoising approach via the nonlinear image-decomposition. In the nonlinear decomposition-and-denoising approach, at the first nonlinear image-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 approximation of the noisy image may not be corrupted by the noise and its texture component may collect almost all the noise. At the successive nonlinear denoising stage, intensity of the separated structural component is utilized instead of the unknown true signal value, to adapt the soft-thresholding-type denoising manipulation of the texture component to the signal dependency of the noise. At the final image-synthesis stage, the separated structure component is combined with the denoised texture component, and thus a sharpness-preserved denoised image is reproduced. The nonlinear decomposition-and-denoising approach selectively removes the signal-dependent noise of a digital camera without not only blurring sharp edges but also destroying visually important textures.