采用零树结构分类小波系数的红外图像降噪

金炜; 周亚训; 符冉迪; 尹曹谦

doi:doi:10.3969/j.issn.1003-501x.2012.05.014

光电工程, 2012, 39 (5): 79, 网络出版: 2012-05-31

采用零树结构分类小波系数的红外图像降噪

Infrared Image Denoising Based on Classified Wavelet Coefficients Using Zerotree Structure

论文大纲

金炜 ^*周亚训符冉迪尹曹谦

作者单位

宁波大学信息科学与工程学院，浙江宁波 315211

红外图像小波系数零树结构降噪 infrared image wavelet coefficient zerotree structure denoising

摘要

红外图像易受噪声污染，为了改善红外图像的质量，提出了一种基于零树结构分类小波系数的红外图像降噪算法。该算法利用小波零树结构表达尺度间的相关性，通过空间自适应阈值将小波系数进行分类，并根据不同类系数的统计特性采用不同的先验分布模型，在贝叶斯框架下实现降噪。实验结果表明，本文算法在峰值信噪比 (PSNR)指标上优于传统算法；从视觉效果来看，该算法在有效去除图像噪声的同时能较好地保持空间细节，可以满足当前红外图像降噪的需求。

Abstract

Infrared image is vulnerable to noise pollution. In order to improve the quality of the infrared image, a denoising algorithm based on classified wavelet coefficients using zerotree structure was proposed. First, the wavelet coefficients were classified via adaptive threshold by expressing the inter-scale dependencies using zerotree structure. Then, various prior distribution models were adopted to represent various statistic characteristics of different class’s coefficients. Finally, infrared image denoising was implemented by Bayes estimation. Experimental results show that the performance of the proposed algorithm is superior to the traditional algorithms in terms of the Peak Signal to Noise Ratio (PSNR). As for visual quality, the proposed algorithm could reduce the noise effectively and retain more details simultaneously. Therefore, it can meet the general demand of denoising for infrared image.

参考文献

[1] Jones B F，Plassmann P. Digital Infrared Thermal Imaging of Human Skin [J]. IEEE Engineering in Medicine and Biology Magazine(S0739-5175)，2002，21(6)：41-48.

[2] 倪国强，秦庆旺，肖蔓君，等 . 中国红外成像技术发展的若干思考 [J].科技导报， 2008，26(22)：88-93. NI Guo-qiang，QIN Qing-wang，XIAO Man-jun，et al. Development of Infrared Imaging Technology in China [J]. Science & Technology Review，2008，26(22)：88-93.

[3] 王怀野，张科，李言俊 . 各向异性滤波在红外图像处理中的应用 [J].红外与毫米波学报， 2005，24(2)：109-113. WANG Huai-ye，ZHANG Ke，LI Yan-jun. Anisotropic Gaussian Filtering for Infrared Image [J]. Journal Infrared Millimeter and Waves，2005，24(2)：109-113.

[4] ChenGY，Bui T D，Krzyzak A. Image denoising using neighbouring wavelet coefficients [J]. Integrated Computer-Aided Engineering(S1069-2509)，2005，12(1)：99-107.

[5] 周扬，吕进，刘铁兵，等 . 小波域高斯混合模型方差估计近红外降噪方法 [J].光电工程， 2011，38(8)：96-100. ZHOU Yang，Lü Jin，LIU Tie-bing，et al. NIR Spectroscopy Noise Reduction Method Using Noise Variance Estimation by Gaussian Mixture Model in Wavelet Domain [J]. Opto-Electronic Engineering，2011，38(8)：96-100.

[6] 宋坤坡，夏顺仁，徐清 . 考虑小波系数相关性的超声图像降噪算法 [J].浙江大学学报：工学版， 2010，44(11)：2203-2208. SONG Kun-po，XIA Shun-ren，XU Qing. Algorithm considering correlation of wavelet coefficients for ultrasound image denoising [J]. Journal of Zhejiang University：Engineering Science，2010，44(11)：2203-2208.

[7] Artur L，David B，Nishan C. Non-Gaussian model-based fusion of noisy images in the wavelet domain [J]. Computer Vision and Image Understanding(S1077-3142)，2010，114(1)：54-65.

[8] Shapiro J M. Embedded image coding using zerotrees of wavelets coefficients [J]. IEEE Trans. on Signal Proc(S1053-587X)， 1993，41(12)：3445-3462.

[9] QiuPH，Mukherjee P S. Edge structure preserving image denoising [J]. Signal Processing(S0165-1684)，2010，90(10)： 2851-2862.

[10] Mallat S. A Wavelet Tour Guide of Signal Processing [M]. San Diego：Academic Press，1999：80-150.

[11] Mihcak M，Kozintsev I，Ramchandran K，et al. Low-complexity image denoising based on statistical modeling of wavelet coefficients [J]. IEEE Signal Processing Letters(S1070-9908)，1999，6(12)：300-303.

[12] Mihcak M，Kozintsev I，Ramchandran K. Spalially adaptive statistical meodeling of wavelet image coefficients and its application to denoising [C]// IEEE International Conference on Acoustics，Speech and Signal Processing，Phoenix，March 15-19，1999：3253-3256.

金炜, 周亚训, 符冉迪, 尹曹谦. 采用零树结构分类小波系数的红外图像降噪[J]. 光电工程, 2012, 39(5): 79. JIN Wei, ZHOU Ya-xun, FU Ran-di, YING Cao-qian. Infrared Image Denoising Based on Classified Wavelet Coefficients Using Zerotree Structure[J]. Opto-Electronic Engineering, 2012, 39(5): 79.

采用零树结构分类小波系数的红外图像降噪

关于本站 Cookie 的使用提示

全站搜索

采用零树结构分类小波系数的红外图像降噪

相关论文

相关资讯

关于本站 Cookie 的使用提示

全站搜索