Image denoising based on edge detection and prethresholding Wiener filtering of multi-wavelets fusion

In this paper, we describe a method for removing Gaussian noise from digital images, based on edge detection and prethresholding Wiener filtering of multi-wavelets fusion. First, we decompose the noisy image by using multiple wavelets, then the edge of image is detected via wavelet multi-scale edge detection. On this basis, the wavelet coefficients belonging to the edge position are dealt with the improved wavelet threshold method and the others are dealt with the prethresholding Wiener filtering. Finally, we use the fusion algorithm based on wavelet analysis to obtain the denoised image. The experimental results show that this method not only can remove the noise without blurring the edges and the important characteristics of the images effectively, but also can highlight the characteristics of image edge compared with the existing methods. The denoised images have higher peak signal to noise ratio (PSNR) and mean structural similarity (MSSIM), hence the method is of great application value.