RETRACTED ARTICLE: Super-resolution restoration of degraded image based on fuzzy enhancement

Abstract

In order to improve the effectiveness of traditional super-resolution restoration methods of degraded image, a method based on fuzzy enhancement is proposed. After wavelet transform, the wavelet coefficients of the degraded image signal and the wavelet coefficients of noise show different characteristics on different scales. Through constructing corresponding rules, wavelet signal de-noising can be achieved. Fuzzy enhancement algorithm is used to enhance the edge of the low-resolution image block from the training set, so that the extracted feature information is more accurate. Content-related samples are used to train the degraded image, and global constraints are applied to the sparse reconstructed image, so as to make the final estimated image close to the original image and realize super-resolution restoration of the degraded image. The simulation results show that the proposed method is practical and effective.