Image Processing Based On Wavelet Transform And Partial Differential Equations

Wavelet has its unique advantage in signal analysis and image processing. Wavelet has good localizing quality at time omain and frequency domaind simultaneously and the characteristic of multi-resolution ratio analysis, so it can fulfill all kinds of wave-filtering needs such as low-pass, high-pass, sink wave, random noise denoising. And the use of PDEs in image processing is a new research topic. Its mathematical model can represent image accurately and can solve many complicated problems.Firstly, some kinds of traditional methods using wavelet transform are introduced and the wavelet shrinkage, a simple yet powerful method is particularly presented. And a new method based on wavelet transform and wiener filtering is presented. Secondly, the PDEs applied in modeling for image processing and image denoising are introduced, some examples for image denoising with PDEs are given. Finaly, the relation between wavelet transform and PDEs is summarized, and combined the specialities, a new method based on them is presented.