Neural Architectures for Correlated Noise Removal in Image Processing

Color image processing, impulsive noise removal, color image enhancement

In this paper a novel adaptive filtering scheme for impulsive noise removal in color images is presented. The noise detection algorithm is based on the concept of aggregated distances assigned to the pixels belonging to the filtering window. The value of the difference between the accumulated distance assigned to the central sample and to the pixel with the lowest rank, serves as an indicator o...

Improved BM3D for Correlated Noise Removal

Most of the literature on denoising focuses on the additive-white-gaussian-noise (AWGN) model. However, in many important applicative fields, images are typically affected by non-Gaussian and/or colored noise, in which cases AWGN-based techniques fall much short of their promises. In this paper, we propose a new denoising technique for correlated noise based on the non-local approach. We start ...

Neural architectures for unifying brightness perception and image processing

PATIL, RAJWADE: POISSON NOISE REMOVAL FOR IMAGE DEMOSAICING 1 Poisson Noise Removal for Image Demosaicing

With increasing resolution of the sensors in camera detector arrays, acquired images are ever more susceptible to perturbations that appear as grainy artifacts called ‘noise’. In real acquisitions, the dominant noise model has been shown to follow the Poisson distribution, which is signal dependent. Most color image cameras today acquire only one out of the R, G, B values per pixel by means of ...

Image Processing Architectures