基于场景有序运动的热红外视频去噪方法  

Thermal infrared video denoising method based on sequential scene motion

作　　者：杨暄[1,2] 王义坤 韩贵丞[1] 蔡能斌[3] 亓洪兴 YANG Xuan;WANG Yi-kun;HAN Gui-cheng;CAI Ceng-bin;QI Hong-xing(Key Laboratory of Space Active Opto-Electronics Technology,Shanghai Institute of Technical Physics,Chinese Academy of Sciences,Shanghai 200083,China;University of Chinese Academy of Sciences,Beijing 100049,China;Shanghai Key Lab.of Scene Evidence,Shanghai 200083,China)

机构地区：[1]中国科学院上海技术物理研究所空间主动光电技术重点实验室,上海200083 [2]中国科学院大学,北京100049 [3]上海市现场物证重点实验室,上海200083

出　　处：《激光与红外》2018年第10期1314-1320,共7页Laser & Infrared

基　　金：国家自然科学基金项目(No.41601353)资助

摘　　要：在信号动态范围较小的场景下热红外图像的信噪比偏低,同时在诸多应用中其场景会在某一方向发生单调运动。基于这种考虑,提出了一种基于场景有序运动的热红外视频去噪方法。通过低秩矩阵近似的相关理论,引入场景有序运动这一先验知识并构建严格的观测矩阵,利用加权核范数最小化算法求解去噪的低秩矩阵形式并重构视频信号。经仿真分析,本方法在强噪声环境下具有较高的峰值信噪比与降噪鲁棒性,通过海洋遥感数据验证了方法的实际效果,从而在遥感与搜救等领域具有一定应用价值。The thermal infrared image has lower signal-to-noise ratio （SNR） in a scene with small signal dynanfic range. In many real applications, the scene is towards one continuous monotonous direction. Under this consideration, a scene-based video denoising method was proposed. By using low rank matrix approximation （LRMA） theory, a prior knowledge was introduced to construct strict observations. The denoising low-rank matrix of observations was solved via weighted nuclear norm nfininfization （WNNM） and then reconstructed video signal. Sinmlation showed that the method had high peak signal-to-noise ratio （PSNR） and denoising robustness. Processed data of ocean remote sensing veri- fied the practical effect of the method. The method has certain application value in a field of remote sensing and rescue.

关 键 词：热红外视频 场景有序运动 低秩矩阵近似 去噪 

分 类 号：TP751.1[自动化与计算机技术—检测技术与自动化装置]