Adaptive de-noising of images by locally switching wavelet transforms
Hakan Öktem, Karen Egiazarian, Vladimir Y. Katkovnik · 2003
A local adaptive image de-noising method based on local selection of the best wavelet, among a finite set, within a sliding window at each level of decomposition is developed. The proposed method suggests certain advantages in terms of de-noising efficiency and detail preservation especially when the image includes different regions which may be efficiently represented by different bases or a priori information on the image is limited. This work concerns the method of using an adaptively varying base and the best wavelet selection rule. The method is implemented and comparative results are submitted.