Many existing techniques for image denoising can be expressed in terms of minimizing a particular cost function. We address the problem of denoising images in a novel way by iteratively refining the cost function. This allows us some control over the trade-off between the bias and variance of the image estimate. The result is an improvement in the mean-squared error as well as the visual quality of the estimate. We ...
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