Image Denoising and Compression using Wavelate

Abstract

Denosing is one of an essential step to improve the image quality. In this project, image denoising is investigated. After reviewing standard image denoising methods as applied in the spatial, frequency and wavelet domains of the noisy image, the project embarks on the endeavor of developing and experimenting with new image denoising methods based wavelet transforms. Image denoising involves the manipulation of the image data to produce a visually high quality image. Finding efficient image denoising methods is still valid challenge in image processing. Wavelet denoising is an attempts to remove the noise present in the image while preserving the image characteristics, regardless of its frequency content. This project is intended to serve as an introduction to Wavelet processing through a set of Matlab experiments. These experiments will give an overview of three fundamental tasks in signal and image processing: approximation, denoising and compression.