Image Processing for Denoising Using Composite Adaptive Filtering Methods Based on RMSE  

作　　者：Yanlu Chen Ruijie Wang Puming Zong Da Chen Yanlu Chen;Ruijie Wang;Puming Zong;Da Chen(Control Theory and Control Engineering, College of Railway Transportation, Hunan University of Technology, Zhuzhou, China;Inner Mongolia Power Group Xilingol Extra High Voltage Power Supply Company, Xilinhot, China;Inner Mongolia Power Group Limited Liability Company XilinGol Power Supply Branch, Xilinhot, China)

机构地区：[1]Control Theory and Control Engineering, College of Railway Transportation, Hunan University of Technology, Zhuzhou, China [2]Inner Mongolia Power Group Xilingol Extra High Voltage Power Supply Company, Xilinhot, China [3]Inner Mongolia Power Group Limited Liability Company XilinGol Power Supply Branch, Xilinhot, China

出　　处：《Open Journal of Applied Sciences》2024年第3期660-675,共16页应用科学（英文）

摘　　要：As one of the carriers for human communication and interaction, images are prone to contamination by noise during transmission and reception, which is often uncontrollable and unknown. Therefore, how to denoise images contaminated by unknown noise has gradually become one of the research focuses. In order to achieve blind denoising and separation to restore images, this paper proposes a method for image processing based on Root Mean Square Error (RMSE) by integrating multiple filtering methods for denoising. This method includes Wavelet Filtering, Gaussian Filtering, Median Filtering, Mean Filtering, Bilateral Filtering, Adaptive Bandpass Filtering, Non-local Means Filtering and Regularization Denoising suitable for different types of noise. We can apply this method to denoise images contaminated by blind noise sources and evaluate the denoising effects using RMSE. The smaller the RMSE, the better the denoising effect. The optimal denoising result is selected through comprehensively comparing the RMSE values of all methods. Experimental results demonstrate that the proposed method effectively denoises and restores images contaminated by blind noise sources.As one of the carriers for human communication and interaction, images are prone to contamination by noise during transmission and reception, which is often uncontrollable and unknown. Therefore, how to denoise images contaminated by unknown noise has gradually become one of the research focuses. In order to achieve blind denoising and separation to restore images, this paper proposes a method for image processing based on Root Mean Square Error (RMSE) by integrating multiple filtering methods for denoising. This method includes Wavelet Filtering, Gaussian Filtering, Median Filtering, Mean Filtering, Bilateral Filtering, Adaptive Bandpass Filtering, Non-local Means Filtering and Regularization Denoising suitable for different types of noise. We can apply this method to denoise images contaminated by blind noise sources and evaluate the denoising effects using RMSE. The smaller the RMSE, the better the denoising effect. The optimal denoising result is selected through comprehensively comparing the RMSE values of all methods. Experimental results demonstrate that the proposed method effectively denoises and restores images contaminated by blind noise sources.

关 键 词：Blind Denoising Adaptive RMSE Image Restoratio 

分 类 号：TN7[电子电信—电路与系统]