Hyperspectral Unstructured Background Target Detection Approach Based on Object-Oriented Analysis
LIU Kai1, ZHANG Li-fu1*, YANG Hang1, ZHU Hai-tao1, JIANG Hai-ling2, LI Yao1
1. Institute of Remote Sensing Applications, Chinese Academy of Sciences, Beijing 100101, China 2. Institute of Remote Sensing and GIS, Peking University, Beijing 100871, China
Abstract:In order to reduce the limitation in background statistics estimation of unstructured background detector, a small target detection algorithm based on object-oriented analysis was proposed. After segmenting the whole imagery into many fairly homogenous regions using adaptive iterative method, multivariate normality test was applied to choose several optimal object sets which obey the law of normal distribution well. Then, the selected objects would be combined with GLR to perform target detection. This method could make the local background well fit a normal distribution and effectively separate the target signal from background, and meanwhile avoid the contamination effect through the selection of optimal objects. A simulation experiment was conducted on real OMIS data to validate the effectiveness of the proposed algorithm. The detection results were compared with those detected by the unstructured background detector GLR and improved GLR which incorporated K-Means clustering. The results show that the proposed algorithm has better detection performance and lower false alarm probability than other detection algorithms.
[1] ZHANG Liang-pei, ZHANG Li-fu(张良培, 张立福). Hyperspectral Remote Sensing(高光谱遥感). Wuhan: Wuhan University Press(武汉:武汉大学出版社), 2005. [2] Manolakis D, Marden D, Shaw G A. Lincoln Laboratory Journal, 2003, 14:79. [3] Kraut S, Scharf L L. Signal Processing, IEEE Transactions on, 1999, 47: 2538. [4] Robey F C, Fuhrmann D R, Kelly E J, et al. Aerospace and Electronic Systems, IEEE Transactions on, 1992,28:208. [5] Zhang L, Du B, Zhong Y. Geoscience and Remote Sensing, IEEE Transactions on, 2010,48:2633. [6] Caefer C E, Silverman J, Orthal O, et al. Optical Engineering, 2008,47:076402. [7] Funk C C, Theiler J, Roberts D A, et al. Geoscience and Remote Sensing, IEEE Transactions on, 2001,39:1410. [8] Carlotto M J. Geoscience and Remote Sensing, IEEE Transactions on, 2005,43:374. [9] LIU De-lian, ZHANG Jian-qi(刘德连, 张建奇). Journal of Infrared and Millimeter Waves(红外与毫米波学报), 2006,25(3):236. [10] Tichavsky P, Koldovsky Z, Oja E. Signal Processing, IEEE Transactions on, 2006,54:1189. [11] Zhang L,Huang X. Neurocomputing, 2010, 73:927. [12] Johnson B,Xie Z. ISPRS Journal of Photogrammetry and Remote Sensing, 2011. [13] Zhang C,Xie Z. Remote Sensing of Environment, 2012,124:310. [14] Tiwari K, Arora M, Singh D. International Journal of Applied Earth Observation and Geoinformation, 2011,13:730. [15] Matteoli S, Diani M, Corsini G. Optical Engineering, 2010,49:046201. [16] Ma L, Crawford M M, Tian J. Journal of Infrared, Millimeter and Terahertz Waves, 2010,31:753.