An Adaptive Weighted Threshold Image Restoration Method Based on Wavelet Domain

Abstract

Due to the limitation of imaging equipment, the influence of transmission medium and external environment, image quality degradation will inevitably occur in the process of generation, transmission and reception. These degradation not only worsens the visual effect of the image, but also makes the image lose a lot of useful information, which seriously affects image recognition, target detection and other high-level visual analysis. Wavelet analysis can extract useful information from image signal and meanwhile its profound wavelet basis can get adapted to signals of different properties. To better apply wavelet transform into image restoration domain, this paper according to the characteristics of wavelet transform, analyzes the method to select threshold function and the relationship within and between layers of wavelet coefficients, gets a proper threshold weight coefficient and propose an adaptive weighted threshold image restoration method based on wavelet domain, which makes smaller deviation and variance between the de-noised image and the original signal. The experiment result shows that the algorithm of this paper can obtain good subjective and objective image quality and effectively retain most detailed information of the image.

[Retracted] Exploring Wavelet Transform‐Based Image Enhancement Algorithm for Image Restoration of Long March National Cultural Park

“…Currently, image enhancement techniques mostly use both linear and nonlinear approaches. Chen and Guo argued that multilayer grayscale distributions have complex properties that lead to many uncertainties, inaccuracies, and other problems [ 23 ]. Thus, fuzzy set theory can be used for the image processing.…”