DocumentCode :
744533
Title :
Recursive Automatic Target Generation Process in Subpixel Detection
Author :
Chein-I Chang ; Cheng Gao ; Shi-Yu Chen
Author_Institution :
Dept. of Comput. Sci. & Electr. Eng., Univ. of Maryland Baltimore County, Baltimore, MD, USA
Volume :
12
Issue :
9
fYear :
2015
Firstpage :
1848
Lastpage :
1852
Abstract :
Automatic target generation process (ATGP) has been used in a wide range of applications in hyperspectral image analysis. It performs a sequence of orthogonal subspace projections to extract potential targets of interest. This letter presents a recursive version of the ATGP, which is referred to as the recursive ATGP (RATGP) and has three advantages over the ATGP as follows: 1) there is no need of inverting a matrix as the ATGP does for finding each new target; 2) there is a significant reduction in the computational complexity in the hardware design due to its recursive structure; and 3) there is an automatic stopping rule that can be derived by the Neyman-Pearson detection theory to terminate the algorithm.
Keywords :
geophysical image processing; geophysical techniques; hyperspectral imaging; matrix algebra; object detection; ATGP matrix; Neyman-Pearson detection theory; automatic stopping rule; computational complexity; hardware design; hyperspectral image analysis; orthogonal subspace projections; recursive automatic target generation process; recursive version; Algorithm design and analysis; Computational complexity; Hyperspectral imaging; Indexes; Signal processing algorithms; Automatic target generation process (ATGP); orthogonal subspace projection; recursive ATGP (RATGP); virtual dimensionality (VD);
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
Publisher :
ieee
ISSN :
1545-598X
Type :
jour
DOI :
10.1109/LGRS.2015.2431233
Filename :
7137619
Link To Document :
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