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A new color image denoising method in the contourlet domain is proposed for reducing noise in images corrupted by Gaussian noise. This method takes into account the statistical dependencies among the contourlet coefficients of the RGB color channels. To this end, the multivariate Cauchy distribution is employed to capture these inter-channel dependencies. This model is then exploited in a Bayesian...
A new contourlet-based method is introduced for reducing noise in images corrupted by additive white Gaussian noise. This method takes into account the statistical dependencies among the contourlet coefficients of different scales. In view of this, a non-Gaussian multivariate distribution is proposed to capture the across-scale dependencies of the contourlet coefficients. This model is then exploited...
There are a number of image denoising methods in the wavelet domain using statistical models. It is known that the performance of such methods can be significantly improved by taking into account the statistical dependencies between the wavelet coefficients. It is shown that the vector-based hidden Markov model (VB-HMM) is capable of capturing both the subband marginal distribution and the inter-scale,...
Statistical image modeling has attracted great attention in the field of image denoising. In this work, a new image denoising method in the contourlet domain is introduced in which the contourlet coefficients of images are modeled by using the Bessel k-form prior. A noisy image is decomposed into a low frequency approximation sub-image and a series of high frequency detail sub-images at different...
In this paper, a new contourlet-based method for denoising of images corrupted by additive white Gaussian noise is proposed. The alpha-stable distribution is used to model the contourlet coefficients of noise-free images. This model is then exploited to develop a Bayesian minimum mean absolute error estimator. A modified empirical characteristic function-based method is employed for estimating the...
Denoising problems can be regarded as that of a prior probability modeling in an estimation task. The performance of the estimator is intimately related on the correctness of the model. This paper proposes a new wavelet-domain image denoising method using the minimum mean square error (MMSE) estimator. The vector-based hidden Markov model (HMM) is used as the prior for modeling the wavelet coefficients...
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