Image denoising via wavelet threshold: single wavelet and multiple wavelets transform

Removing noise from the original image is still a challenging problem for researchers. There have been many published methods based on wavelet-transform (WT) and each one has its assumptions, advantages, and limitations. Many of these methods are built in the single wavelet framework. Recently multiple wavelets have been formulated. As in the single wavelet case, the theory of multiple wavelets is based on the idea of multi-resolution analysis (MRA). The difference between single wavelet and multiple wavelets is that the former has one scaling function while the later has several scaling functions. In this paper we make a comparison between image denoising by single wavelet and by multiple wavelets. Experimental results show that multiple wavelets generally outperform single wavelet in image denoising.