Synthetic aperture radar (SAR) images are inherently degraded by multiplicative speckle noise where thresholdingbased methods in the transform domain are appropriate. Being sparse, the coefficients in the transformed domain play a key role in the performance of any thresholding methods. It has been shown that the coefficients of nonsubsampled shearlet transform (NSST) are sparser than those of ...

In this paper we propose the use of a new implementation of the hyperanalytic wavelet transform, (HWT), in association with a Maximum a Posteriori (MAP) filter named bishrink. Such a denoising method is sensitive to the selection of the mother wavelets used for the computation of the HWT. Taking into account the drawbacks of the bishrink filter and the sensibility with the selection of the moth...

We propose the use of a new implementation of the hyperanalytic wavelet transform, (HWT), in association with a Maximum a Posteriori (MAP) filter named bishrink. The denoising methods based on wavelets are sensitive to the selection of the mother wavelets. Taking into account the drawbacks of the bishrink filter and the sensitivity with the selection of the mother wavelets we propose a denoisin...

This paper presents a new denoising method for base-band communication signals corrupted by additive noise. The novelty of this paper is the use of a special MAP filter, called composed bishrink, for communication purposes. A complete statistical analysis of this filter is reported. Some simulations are presented. The results obtained are compared with the results of matched filtering technique...

This paper presents a new denoising method in the wavelet domain, which aims to reduce the noise, preserving the structural features (like the discontinuities) and textural information of the scene. In this paper we propose the association of the Double Tree Complex Wavelet Transform, (DT-CWT) with a Maximum A Posteriori (MAP) filter named bishrink. The corresponding denoising algorithm is simp...

The performance of image denoising algorithms using the Double Tree Complex Wavelet Transform, DT CWT, followed by a local adaptive bishrink filter can be improved by reducing the sensitivity of that filter with the local marginal variance of the wavelet coefficients. In this paper is proposed a solution for the sensitivity reduction based on enhanced diversity.