自动化学报Issue(2)：290-298,9.DOI:10.16383/j.aas.2016.c150196
结合多种特征的高分辨率遥感影像阴影检测
Shadow Detection in High Resolution Remote Sensing Images Using Multiple Features
摘要
Abstract
To aim at the problem that shadow detection algorithms cannot simultaneously well detect partial-bright shadows and shadows in dark object, a kind of high resolution remote sensing images shadow detection method that combine a multiple features is proposed. The algorithm firstly combines principal component analysis, color features and histogram segmentation to construct the detection conditions of various thresholds, then integra various features of remote sensing image for initial detection, finally by analyzing the difference of the RGB models in the shadow and non shadow, uses the color characteristics to detect the shadow region. Experimental results show that the algorithm proposed in this paper can detect partial uses bright shadows and shadows in dark object effectively. Compared with the existing methods, the average total error rate goes from the level set method 31.85% down to 24.61% for partial shadow, and the average total error rate is reduced from the automatic detection method 37.75%to 23.30%for shadows in dark object.关键词
高分辨率遥感影像/阴影检测/主成分分析/颜色特征/直方图的分割Key words
High resolution remote sensing images/shadow detection/principal component analysis/color features/histogram segmentation引用本文复制引用
张先鹏,陈帆,和红杰..结合多种特征的高分辨率遥感影像阴影检测[J].自动化学报,2016,(2):290-298,9.基金项目
国家自然科学基金(61373180,61461047),西南交通大学2015年研究生创新实验实践项目(YC201504106)资助@@@@Supported by National Natural Science Foundation of China (61373180,61461047) and Southwest Jiaotong University Grad-uate Student Innovation Experiment Project in 2015(YC201504106) （61373180,61461047）
