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Algorithm and Realization on Image Denoising Based on Wavelet Transform

Author: YuanHongMei
Tutor: ChenWen；GanYu
School: Shanghai Jiaotong University
Course: Electronics and Communication Engineering
Keywords: Wavelet Transform Image processing Wavelet Denoising Soft Hard threshold Image singularity
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 861
Quote: 14
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Abstract


Image acquisition , acquisition and transfer process , often subject to noise pollution , noise pollution image called noisy image . The noise is the main factors affecting the image quality , all kinds of noise affect people necessary information to be extracted from the image noise cancellation is an old topic in image processing . Recent years , wavelet theory has been very rapid development , wavelet analysis is a localized time-frequency analysis , which uses time domain and frequency domain joint represents the characteristics of the signal , a powerful tool for the analysis of non - stationary signals through the telescopic arithmetic functions , translation and other refined multi-scale analysis of the signal can be effectively extracted from the signal information. Wavelet analysis is internationally recognized signal and information processing field of high-tech , cutting-edge topics and research focus of the signal processing , signal filtering , denoising , image compression , image edge detection, image fusion applications increasingly attention has been paid . This paper studies the wavelet theory applications in signal and image denoising . The main work done in this paper are as follows : comprehensive description of wavelet image denoising technology development in history and technical development of the status quo , and also pointed out that the the wavelet denoising advantages compared with other conventional methods , and carry out wavelet image denoising coding research significance . Wavelet image denoising theory based on the summary of the mathematical properties of the wavelet of wavelet transform , multi - resolution analysis and image denoising with compression of theoretical knowledge . The signal denoising technology , focus on threshold method proposed by Donoho denoising . According to this feature soft thresholding and hard threshold method . This method is based on the simulation , using Daubechies 4 single wavelet denoising noisy signal . The experiments show that the method can further improve the signal-to-noise ratio , denoising effect is very obvious . In this paper, a selected threshold based on the image singularity wavelet shrinkage , experiments show that this method can better denoising .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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