Shadow Detection in Remotely Sensed Images Based on Self-Adaptive Feature Selection

被引:58
|
作者
Liu, Jiahang [1 ,2 ,3 ]
Fang, Tao [1 ,2 ]
Li, Deren [4 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Automat, China Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
[2] Shanghai Jiao Tong Univ, Minist Educ, China Key Lab Syst Control & Informat Proc, Shanghai 200240, Peoples R China
[3] Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian 710119, Peoples R China
[4] Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan 430079, Peoples R China
来源
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING | 2011年 / 49卷 / 12期
基金
中国国家自然科学基金;
关键词
Chromatic information; image analysis; image segmentation; remotely sensed image; self-adaptive feature selection (SAFS); shadow detection; shadow property; COLOR; BUILDINGS;
D O I
10.1109/TGRS.2011.2158221
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Shadows in remotely sensed images create difficulties in many applications; thus, they should be effectively detected prior to further processing. This paper presents a novel semiautomatic shadow detection method that meets the requirements of both high accuracy and wide practicability in remote sensing applications. The proposed method uses only the properties derived from the shadow samples to dynamically generate a feature space and calculate decision parameters; then, it employs a series of transformations to separate shadow and nonshadow regions. The proposed method can detect shadows from both color and gray images. If the chromatic properties of color images do not agree with the defined rules through the shadow samples, then the shadow detection process will automatically reduce to the process for gray images. As the shadow samples are manually selected from the input image by the user, the derived parameters conform well to the characteristics of the input image. Experiments and comparisons indicate that the proposed self-adaptive feature selection algorithm is accurate, effective, and widely applicable to shadow detection in practical applications.
引用
收藏
页码:5092 / 5103
页数:12
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