A multiresolution framework for local similarity based image denoising

Abstract

In this paper, we present a generic framework for denoising of images corrupted with additive white Gaussian noise based on the idea of regional similarity. The proposed framework employs a similarity function using the distance between pixels in a multidimensional feature space, whereby multiple feature maps describing various local regional characteristics can be utilized, giving higher weight to pixels having similar regional characteristics. An extension of the proposed framework into a multiresolution setting using wavelets and scale space is presented. It is shown that the resulting multiresolution multilateral (MRM) filtering algorithm not only eliminates the coarse-grain noise but can also faithfully reconstruct anisotropic features, particularly in the presence of high levels of noise.

A novel Non-local means image denoising method based on grey theory

“…In other words, our method is suitable to different values of P . We shall have a special interest in 1 l due to the tendency to sparse the solution.…”

“…Image denoising is an active topic in image processing domain [1,2]. Its purpose is to restore the original image from noisy data.…”

Content adaptive video denoising based on human visual perception

“…Thus, we perform nonlocal mean filtering only in complex regions to reduce the computational cost. Moreover, signal processing for image denoising have been discussed in the literature [11][12][13][14][15][16][17][18][19][20][21][22][23]. Although spatial filtering was able to preserve the motion of video sequences, it failed to remove noise sufficiently and caused the flicker in a wide range of noise distribution where the noise artifacts covered many pixels over a number of levels.…”

An In-field Calibrated Multiband-Multiresolution Bilateral Filter for Digital Image Applications

“…Some works have proposed to embed bi-dimensional bilateral filters (2D-BF) in wavelet denoising methods -specifically on the LL sub-band and on the reconstructed image -in order to optimize noise filtering without compromising the edge preservation. This new approach is referred to as multiresolution bilateral filter (MBF) [15] [16] [17].…”