NSCT域红外图像改进非局部均值滤波算法.pdfVIP

第37 卷 第1 期 红 外 技 术 Vol.37 No.1 2015 年1 月 Infrared Technology Jan. 2015 NSCT 域红外图像改进非局部均值滤波算法 韩红光 （浙江农业商贸职业学院基础教学部，浙江绍兴 312088 ） 摘要：结合非下采样轮廓波变换（NSCT ），提出了一种红外图像改进非局部均值滤波算法（Improved Non-local Means Filtering ，INLMF ）。该算法首先对红外噪声图像进行多尺度NSCT 变换，其次分别从 相似图像块自适应划分方法以及滤波权重计算方法 2 个方面对经典非局部均值滤波算法进行适当改 进，将改进后的非局部均值滤波算法（INLMF ）应用于处理高频分解系数，然后将滤波后的高频分解 系数与低频分解系数进行重构，得到去噪后的图像，最后对去噪后图像采用非负支撑域有限递归逆滤 波（Non-negativity and Support Constraints Recursive Inverse Filtering ，NAS-RIF ）算法进行图像复原， 以尽可能消除因滤波造成的图像失真。测试结果表明，本文算法滤波效果优于 NLMF 及其已有的改进 算法。 关键词：红外图像处理；非下采样轮廓波变换；非局部均值滤波；非负支撑域有限递归逆滤波算法 中图分类号：TP391.41 文献标识码：A 文章编号：1001-8891(2015)01-0034-05 Improved Non-local Means Infrared Image Filtering Algorithm Based on NSCT HAN Hong-guang (Basic Teaching Department, Zhejiang Agricultural Business College, Shaoxing Zhejiang 312088, China) Abstract ：Combined with nonsubsampled contourlet transform, an improved non-local means infrared image filtering algorithm is proposed. Firstly, the infrared image noise is conducted by nonsubsampled contourlet transform. Then, the similarity image block adaptive partition method and weighting calculation method are proposed so as to improve the non-local means filtering algorithm(INLMF) to deal with the high-frequency NSCT coefficients. Thirdly, the high-frequency NSCT coefficients after filtering and low-frequency NSCT coefficients are reconstructed and the denoised image is obtained. Finally, the denoised image is processed by the non-negativity and support const