Approach of Image Denoising Based on Discrete Multi-Wavelet Transform

A new approach by using discrete multi-wavelet transform to remote sensing image denoising is presented. The wavelet theories have given rise to the wavelet thresholding method, for extracting a signal from noisy data. Multi-wavelets can offer simultaneous orthogonality, symmetry and short support, and these properties make multi-wavelets more suitable for various image processing applications, especially denoising. Denoising of images via thresholding of the multi-wavelet coefficients result from pre-processing and the multi-wavelet transform can be carried out by treating the output in this paper. Multi-wavelet transform technique has a big advantage over the other techniques that it less distorts spectral characteristics of the image denoising. The form of the threshold is carefully formulated and is the key to the excellent results obtained in the extensive numerical simulations of image denoising. The experimental results show that multi-wavelet on image denoising schemes outperform wavelet-based method both in subjectively and objectively.