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In this letter, we present an efficient algorithm for the removal of random-valued impulse noise from a corrupted image by using a reference image. The proposed method uses a statistic of rank-ordered relative differences to identify pixels which are likely to be corrupted by impulse noise. Once a noisy pixel is identified, its value is restored by a simple(More)
This correspondence proposes an efficient algorithm for removing Gaussian noise from corrupted image by incorporating a wavelet-based trivariate shrinkage filter with a spatial-based joint bilateral filter. In the wavelet domain, the wavelet coefficients are modeled as trivariate Gaussian distribution, taking into account the statistical dependencies among(More)
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