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Proceedings Paper

Progressive constrained energy minimization for subpixel detection
Author(s): Yulei Wang; Robert Schultz; Shih-Yu Chen; Chunhong Liu; Chein-I Chang
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Paper Abstract

Constrained energy minimization (CEM) has been widely used for subpixel detection. It makes use of the sample correlation matrix R by suppressing the background thus enhancing detection of targets of interest. In many real world problems, implementing target detection on a timely basis is crucial, specifically moving targets. However, since the calculation of the sample correlation matrix R needs the complete data set prior to its use in detection, CEM is prevented from being implemented as a real time processing algorithm. In order to resolve this dilemma, the sample correlation matrix R must be replaced with a causal sample correlation matrix formed by only those data samples that have been visited and the currently being processed data sample. This causality is a pre-requisite to real time processing. By virtue of such causality, designing and developing a real time processing version of CEM becomes feasible. This paper presents a progressive CEM (PCEM) where the causal sample correlation matrix can be updated sample by sample. Accordingly, PCEM allows the CEM to be implemented as a causal CEM (C-CEM) as well as real time (RT) CEM via a recursive update equation in real time.

Paper Details

Date Published: 18 May 2013
PDF: 7 pages
Proc. SPIE 8743, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX, 874321 (18 May 2013); doi: 10.1117/12.2015447
Show Author Affiliations
Yulei Wang, Harbin Engineering Univ. (China)
Univ. of Maryland, Baltimore County (United States)
Robert Schultz, Univ. of Maryland, Baltimore County (United States)
U.S. Naval Academy (United States)
Shih-Yu Chen, Univ. of Maryland, Baltimore County (United States)
Chunhong Liu, Univ. of Maryland, Baltimore County (United States)
China Agricultural Univ. (China)
Chein-I Chang, Univ. of Maryland, Baltimore County (United States)


Published in SPIE Proceedings Vol. 8743:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XIX
Sylvia S. Shen; Paul E. Lewis, Editor(s)

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