Open AccessAn Adaptive Weighted Threshold Image Restoration Method Based on Wavelet Domain
Author(s) -
Lili Chen,
Hongjun Guo
Publication year - 2021
Publication title -
international journal of circuits, systems and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.156
H-Index - 13
ISSN - 1998-4464
DOI - 10.46300/9106.2021.15.34
Subject(s) - wavelet , artificial intelligence , wavelet transform , computer vision , image restoration , image (mathematics) , computer science , image quality , second generation wavelet transform , pattern recognition (psychology) , stationary wavelet transform , wavelet packet decomposition , mathematics , image processing
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.