Memristor bridge-based low pass filter for image processing

作     者：YU Yongbin YANG Nijing YANG Chenyu NYIMA Tashi 

作者机构：School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu 610054 China School of Information Science and Technology Tibet University Lhasa 850012 China 

出 版 物：《Journal of Systems Engineering and Electronics》 (系统工程与电子技术（英文版）)

年 卷 期：2019年第30卷第3期

页      面：448-455页

核心收录：

学科分类：07[理学] 08[工学] 

基　　金：supported by the National Natural Science Foundation of China(61550110248) 

主　　题：memristor bridge low-pass filter (LPF) adaptive Gaussian filter image denoising Gaussian pyramid 

摘      要：This paper highlights the memristor bridge-based lowpass filter (LPF) and improved image processing algorithms along with a novel adaptive Gaussian filter for denoising image and a new Gaussian pyramid for scale invariant feature transform (SIFT). First, a novel kind of LPF based on the memristor bridge is designed, whose cut-off frequency and other traits are demonstrated to change with different time and memristance. In light of the changeable parameter of the memristor bridge-based LPF, a new adaptive Gaussian filter and an improved SIFT algorithm are presented. Finally, experiment results show that the peak signalto- noise ratio (PSNR) of our denoising is bettered more than 2.77 dB compared to the corresponding of the traditional Gaussian filter, and our improved SIFT performances including the number of matched feature points and the percent of correct matches are higher than the traditional SIFT, which verifies feasibility and effectiveness of our algorithm.