Image denoising based on dual tree complex wavelet transform and bilateral filter
WAN Liyong1,2， CHEN Jiayi3
(1.School of Artificial Intelligence， Nanchang Institute of Science and Technology， Nanchang 330108， China； 2.Management Science and Engineering Research Center， Jiangxi Normal University， Nanchang 330046， China； 3.School of Information Engineering， Guangdong Medical University， Zhanjiang， Guangdong 524023， China)
Abstract：To break through the bottleneck of the existing Gaussian noise reduction methods， an image denoising method based on dual tree complex wavelet transform and bilateral filter is proposed. Based on the distribution characteristic of the image and noise， an adaptive threshold denoising model is derived. By the adaptive threshold denoising model， the image coefficients by dual tree complex wavelet transform are quantitatively processed， and the denoised image is obtained by the inverse dual tree complex wavelet transform. And then the edge of denoised image is enhanced by the improved bilateral filter， in which the bilateral filtering kernel is adaptive to image features， showing better robustness. The experimental results show that the PSNR achieved by the proposed method is about 0.8 dB higher than that of existing fairly good methods， and the SSIM is about 2.5% higher. The experiments confirm is superior to the existing methods in noise removal and edge restoration.
万里勇,陈家益. 基于双树复小波变换与双边滤波的图像滤波[J]. 华中师范大学学报(自然科学版), 2021, 55(6): 1030-1036.
WAN Liyong,CHEN Jiayi. Image denoising based on dual tree complex wavelet transform and bilateral filter. journal1, 2021, 55(6): 1030-1036.
2021, Vol. 55 
