Image Denoising and Compression using Wavelate

International Journal of Electronics and Communication Engineering

© 2016 by SSRG - IJECE Journal

Volume 3 Issue 4

Year of Publication : 2016

Authors : Nikhil D. Chauhan, Naman Gandhi, Khushbu Joshi and Reena Patel

10.14445/23488549/IJECE-V3I4P102

How to Cite?

Nikhil D. Chauhan, Naman Gandhi, Khushbu Joshi and Reena Patel, "Image Denoising and Compression using Wavelate," SSRG International Journal of Electronics and Communication Engineering, vol. 3,  no. 4, pp. 6-9, 2016. Crossref, https://doi.org/10.14445/23488549/IJECE-V3I4P102

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.

Keywords:

Image-denoising,Wavelets, Wavelet Thresholding,Image Processing.

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