Algorithm And Realization On Image Denoising Based On Wavelet Transform

The image is often corrupted by noise in its collection, acquisition or transmission, The corrupted image is called noisy image. Because the noise is the main factor that influenced image quality and greatly affected to extract the information from it, therefore, denoising is a task of great antiquity.In the recent few years , wavelet theory has got great progress. Wavelet analysis is local analysis in the time domain and frequency domain, and which represents the signal property using combination of the time domain and frequency domain. It is a useful tool to analyze the unstationary signal that implements multiscale analysis to the signal by the translation and dilation of the mother wavelet. So it can effectively extract information from signal. At present, wavelet analysis is international acknowledged advanced technology in the domain of information and signal processing. Meanwhile it is the front question for discuss and study hotspot attached more and more importance to people in the domain such as signal filtering, image de-noising, image coding , image edge detecting, image fusing etc.This dissertation mainly studies the wavelet theory and its appliance in image de-noising. The main works of this dissertation are as fellows: This dissertation introduces the history and the state of arts of image de-noising and coding. Meanwhile, it also points out the advantages of wavelet other traditional methods and the importance of developing the study of wavelet image de-noising and image coding. Also it elaborates some basic theories about the wavelet image de-noising and compression, especially on kinds of wavelet transforms, multi-resolution analysis etc. in addition, the dissertation introduces some kinds of method of general de-noising technology, and in particular worked over the threshold de-noising method advanced by Donoho. And based on this, it put forward the soft & hard threshold method. In the emulate experiment, it used the Daubchies wavelet to de-noise the noisy signal,and was shown that it can upgrad the SNR greatly with a signifigant result in the image process.