We propose a novel image denoising strategy based on an enhanced sparse representation
in transform domain. The enhancement of the sparsity is achieved by grouping similar 2D …

In order to resolve the problem that the denoising performance has a sharp drop when noise
standard deviation reaches 40, proposed to replace the wavelet transform by the DCT. In …

We propose an image restoration technique exploiting regularized inversion and the recent
block-matching and 3D filtering (BM3D) denoising filter. The BM3D employs a non-local …

This correspondence proposes an efficient algorithm for removing Gaussian noise from
corrupted image by incorporating a wavelet-based trivariate shrinkage filter with a spatial …

We present a novel approach to still image denoising based on effective filtering in 3D
transform domain by combining sliding-window transform processing with block-matching …

BM3D is a recent denoising method based on the fact that an image has a locally sparse
representation in transform domain. This sparsity is enhanced by grouping similar 2D image …

We propose an effective color image denoising method that exploits filtering in highly sparse
local 3D transform domain in each channel of a luminance-chrominance color space. For …

Collaborative filters perform denoising through transform-domain shrinkage of a group of
similar patches extracted from an image. Existing collaborative filters of stationary correlated …

Single image denoising suffers from limited data collection within a noisy image. In this
paper, we propose a novel image denoising scheme, which explores both internal and …

Most existing state-of-the-art image denoising algorithms are based on exploiting similarity
between a relatively modest number of patches. These patch-based methods are strictly …