基于双树复小波变换的BivaShrink自选窗图像去噪算法  

BivaShrink Adaptive Select Window Image Denoising Algorithm Based on DTCWT

作　　者：付康[1,2] 汤辉[1,2] 孙丹[1,2] 刘波平[1,2] 王蕾[1,2] FU Kang TANG Hui SUN Dan LIU Bo-ping WANG Lei(Jiangxi Institute of Computing Technology, Nanchang,Jiangxi 330003,China Software Engineering and Technical Research Center of Jiangxi Province, Nanchang,Jiangxi 330003,China)

机构地区：[1]江西省计算技术研究所,江西南昌330003 [2]江西省软件工程技术研究中心,江西南昌330003

出　　处：《计算技术与自动化》2017年第1期108-112,共5页Computing Technology and Automation

基　　金：国家科技支撑计划项目"特色区域农村信息化集成技术与应用"(2014BAD10B00)子课题"中部经济区农村信息化技术集成应用"(2014BAD10B05)

摘　　要：在小波变换理论和双变量模型的研究基础上,本文提出了一种BivaShrink自选窗算法,该算法根据邻域内小波系数的相关度大小自适应选取邻域窗口。最后将双树复小波变换应用在BivaShrink自选窗图像去噪算法中。实验结果证明,BivaShrink自选窗优于BivaShrink去噪算法,与传统的离散小波变换相比,双树复小波自选窗图像去噪效果优于BivaShrink自选窗。Based on wavelet transform and bivariate model,this paper proposed an adaptive select window algorithm of BivaShrink,it adaptive select neighborhood Window according to the correlation degree of wavelet coefficients. Finally the DTCWT apply in the algorithm. Experimental tests reveal that adaptive select window algorithm of BivaShrink is better than BivaShrink,compared with traditional discrete wavelet transform, the algorithm apply on DTCWT is better than daptive select window algorithm of BivaShrink.

关 键 词：小波变换 图像去噪 双变量模型 双树复小波变换 

分 类 号：TN911.73[电子电信—通信与信息系统]