Paper
22 October 2004 Robust approach to the MAD change detection method
Lu Zhang, Mingsheng Liao, Yan Wang, Lijun Lu, Yong Wang
Author Affiliations +
Abstract
Digital change detection using multi-temporal remotely sensed imagery is a key topic in the studies of the global environmental changes. Significant efforts have been made in the development of methods for digital change detection. Among the methods, the multivariate alteration detection (MAD) shows great promising. However, the use of mean and covariance matrix of feature vectors in the method makes the detection non-robust because the mean and covariance matrix are influenced by the presence of outliers. In this article two schemes are proposed to improve the robustness of the MAD method. The two schemes, based on different strategies of outlier handling, consist of a two-pass and a one-pass processing, respectively. Finally a preliminary study was carried out to evaluate the feasibility and effectiveness of the proposed schemes.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Lu Zhang, Mingsheng Liao, Yan Wang, Lijun Lu, and Yong Wang "Robust approach to the MAD change detection method", Proc. SPIE 5574, Remote Sensing for Environmental Monitoring, GIS Applications, and Geology IV, (22 October 2004); https://doi.org/10.1117/12.565389
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Cited by 6 scholarly publications.
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KEYWORDS
Statistical analysis

Remote sensing

Matrices

Earth observing sensors

Canonical correlation analysis

Clouds

Landsat

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