We study a central difference discretization of Rudin-Osher-Fetami model for image de-noising. We show that the discrete solution uk converges to the continuous solution u in L2 norm and a rate of convergence is given.

Introduction: SPECT is a diagnostic imaging technique the main disadvantage of which is the existence of Poisson noise. So far, different methods have been used by scientists to improve SPECT images. The Wavelet Transform is a new method for de-noising which is widely used for noise reduction and quality enhancement of images. The purpose of this paper is evaluation of noise reduction in SPECT ...

Abstract This chapter is devoted to random and memory-free methods that repeatedly construct solutions or modify them. Among the most popular techniques, there are simulated annealing, threshold accepting, great deluge demon algorithms, noising methods, late acceptance hill climbing, variable neighborhood search, GRASP.

This paper presents an approach which addresses both de-noising and contrast enhancement. In a multiscale wavelet analysis framework, we take advantage of both soft thresholding and hard thresholding wavelet shrinkage techniques to reduce noise. In addition, we carry out nonlinear processing to enhance contrast within structures and along boundaries. Feature restoration and enhancement are acco...

Received Jul 8, 2017 Revised Nov 20, 2017 Accepted Dec 11, 2017 This paper presents a novel audio de-noising scheme in a given speech signal. The recovery of original from the communication channel without any noise is a difficult task. Many de-noising techniques have been proposed for the removal of noises from a digital signal. In this paper, an audio denoising technique based on Short Time F...

Wavelets provide a powerful and remarkably flexible set of tools for handling fundamental problems in science and engineering, such as audio de-noising, signal compression, object detection and fingerprint compression, image de-noising, image enhancement, image recognition, diagnostic heart trouble and speech recognition, to name a few. Here, we are going to concentrate on wavelet application i...