Abstract :
Image denoising is a lively research field. The classical nonlinear filters used for image denoising, such as median filter, are based on a local analysis of the pixels within a moving window. Recently, the research of image denoising has been focused on the wavelet domain. Compared to the classical nonlinear filters, it is based on a global multiscale analysis of images. Apparently, the wavelet transform can be embedded in a moving window. Thus, a moving window-based local multiscale analysis is obtained. In this paper, based on the Haar wavelet, a class of nonorthogonal multichannel filter bank with its corresponding wavelet shrinkage called Lee shrinkage is derived. As a special case of this filter bank, the double Haar wavelet transform is introduced. Examples show that it is suitable for a moving window-based local multiscale analysis used for image denoising, edge detection, and edge enhancement
Keywords :
Haar transforms; edge detection; image denoising; image enhancement; median filters; wavelet transforms; Lee shrinkage; classical nonlinear filters; edge detection; edge enhancement; global multiscale image analysis; image denoising; image processing; median filter; moving window-based double Haar wavelet transform; moving window-based local multiscale analysis; nonorthogonal multichannel filter bank; wavelet shrinkage; Filter bank; Image analysis; Image denoising; Image edge detection; Image processing; Noise reduction; Nonlinear filters; Wavelet coefficients; Wavelet domain; Wavelet transforms; Edge detection; Haar wavelet; Lee shrinkage; edge enhancement; image denoising; moving window;
