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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 and its texture component may collect almost all the noise. At the successive denoising stage, the structural component is used 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, one combines the separated structure component with the denoised texture component to reproduce a denoised image. The approach selectively removes the signal-dependent noise without not only blurring sharp edges but also destroying visually important textures.