摘要
提出了一种基于改进邻域收缩法的NSCT域红外图像去噪算法。首先使用Bayes Shrink自适应阈值取代通用阈值作为改进邻域收缩法中的收缩阈值,再利用该收缩阈值对NSCT分解后的红外图像的高频子带进行系数收缩处理。仿真实验结果表明:改进算法在去噪性能和视觉效果方面相对于实验中的对比方法均有所提高,具有较好的抗噪性能和良好的边缘保护能力,能够有效的用于红外图像的去噪中。
An infrared image de-noising method using improved Neigh-Shrink based on NSCT is presented. First, Bayes-Shrink adaptive threshold replace common threshold as the contraction threshold of the improved Neigh-Shrink is used, and then the high frequency sub-band of infrared image after NSCT decomposition by using the improved Neigh-Shrink is eliminated. Experiment results show that： compared with the comparison of experimental methods, the improved Neigh-Shrink in de-noising performance and visual effects have been improved, with better anti-noise performance and excellent edge protection, and can effectively be used to infrared images de-noising.
出处
《科学技术与工程》
北大核心
2014年第23期103-107,共5页
Science Technology and Engineering
基金
国家自然科学基金项目(61203189)资助
