Image Wavelet Denoising based on Human Vision System Theory

In order to removes the ring effect in traditional image denoising algorithms using wavelet thresholding, the paper analyzes the wavelet coefficients of noise images, uses second-order central moment of HH1 sub-bands as the noise variance and computes threshold values; and then performs wavelet thresholding denoising on each image block. At last, the paper weights these denoised wavelet coefficients using Kaiser Function. Compared with traditional algorithms, because the algorithm in the paper makes use of the characteristics of wavelet coefficients and the Human Vision System Theory, it preserves the edge and texture information and removes the ring effect. Moreover, the algorithm uses Kaiser Function to overcome blocking effects and improves the visual effects of the denoised image.