Variational Approach for Restoring Random-Valued Impulse Noise
We present a modified iterative method for removing random-valued impulse noise. This method has two phases. The first phase uses an adaptive center-weighted median filter to identify those pixels which are likely to be corrupted by noise (noise candidates). In the second phase, these noise candidates are restored using a detail-preserving regularization method which allows edges and noise-free pixels to be preserved. This phase is equivalent to solving a one-dimensional nonlinear equation for each noise candidate. We describe a simple secant-like method to solve these equations. It converges faster than Newton’s method, requiring fewer function and derivative evaluations.
KeywordsIEEE Transaction Noisy Image Impulse Noise Derivative Evaluation Impulse Noise Removal
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