Adaptive Image Denoising Based On Lifting Scheme Wavelet

Image processing is a very important part of modem communicationtechnology and get more and more important in our living and work. but for somereason, there're always lots of noise which will have impact on image analysis andcommunication. for higher quality on that, we have to reduce those noises. typical wayto demoise almost concentrate on patial domain, like mean filters, order-statisticsfilters, adapive filters. recently, wavelet theory got great progress. for it has very goodquality in frequency domain and multiresolution. so it get great success in lots ofapplication. wavelet derived from fourier. and can perform analysis in both spatialdomain and frequency domain. has advantage on checking noise point. so can bemore efficient on find noise point in image.The main research content of this paper consist the following 4 sections:A brief of the development of maveletIntroduce of denoising theory on both spatial and frequency domain, and giveexamples of typical denoise way in spatial domainIntroduce of denoising theory on wavelet, and the detailed information aboutseveral typical wavelet denoising solutions.Introduce a new adaptive wavelet denoising filter, and provide the experiencedata.