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.