The Research Of Image Processing Based On Wavelet Theory

Wavelet analysis is internationally recognized up to the minute tool for analyzing time-frequency. This paper discusses the technique of image processing based onwavelet transform.The fundamental theories of wavelet analysis are discussed in detail. Continuous wavelet transform, discrete wavelet transform and dyadic wavelet transform areintroduced. The fast algorithm of discrete dyadic wavelet transform is given. Finally, an analysis is made on the influence of the wavelet bases on practical applications by studying their mathematical properties.The principles of wavelet transform de-noising method areintroduced in detail, an analysis of the choice of some parameters in the process ofde-noising is made in detail, and some choice grounds are given. Some key problemson de-noising method based on wavelet threshold are discussed in detail, and some improvement schemes are proposed, and the simulation testing has proved the effectiveness of the schemes.The traditional methods of edge detection are based on one-order derivative's maximum, or two-order derivative's zero-crossing. With multi-scale characterization, waveletanalysis was widely used to mufti-scale edge detection. In this paper, it was proved that, wavelet-based mufti-scale edge detection would keep edge positions very well, if symmetric bases were used in wavelet transform. Furthermore, an algorithm ofmufti-scale edge detection based on biorthogonal symmetric wavelet was put forward, with which, "good edges" will be obtained while the edge positions wilt be kept well.According to human vision perception theory, we studied texture feature extraction based on wavelet multi-scale analysis. After reviewing wavelet theory, pyramid wavelet decomposition was introduced to texture representation, we discussed the problem of optimal window size for texture feature extraction method. in view of the fuzzy and stochastic characteristics of the human vision system, we studied fuzzy clustering algorithm; we discussed clustering validity problem, and atexture segmentation method based on adaptive FCM has been constructed by the guidance of fuzzy clustering validity.