Although there has been a lot of progress in the general area of signal denoising, noise
removal remains a very challenging problem in real-world communication systems …

Due to its heavy-tailed and fully parametric form, the multivariate generalized Gaussian
distribution (MGGD) has been receiving much attention in signal and image processing …

The denoising of Gaussian additive white noise is a classical problem in signal and image
processing. In this paper, we classify the most important wavelet denoising methods into …

A visible/near-infrared hyperspectral imaging (HSI) system (400–1000 nm) coupled with
wavelet analysis was used to determine the total volatile basic nitrogen (TVB-N) contents of …

The proposed work deals with image based solar tracker utilizing raspberry pi 4B. The
system works fine with a webcam supporting the digital image processing within the …

The Kullback-Leibler divergence (KLD) between two multivariate generalized Gaussian
distributions (MGGDs) is a fundamental tool in many signal and image processing …

In this work, the authors present an effective denoising method to attempt reducing the noise
in mammographic images. The method is based on using hierarchical correlation of the …

In this paper, we describe an algorithm for computing biorthogonal compactly supported
dyadic wavelets related to the Walsh functions on the positive half-line ℝ+. It is noted that a …

Multivariate generalized Gaussian distributions (MGGDs) have aroused a great interest in
the image processing community thanks to their ability to describe accurately various image …

This paper presents a novel way to reduce noise introduced or exacerbated by image
enhancement methods, in particular algorithms based on the random spray sampling …