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Journal of Applied Remote Sensing

Robust multipixel matched subspace detection with signal-dependent background power
Author(s): Victor Golikov; Marco Rodriguez-Blanco; Olga Lebedeva
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Paper Abstract

A modified matched subspace detector (MSD) has been recently proposed for detecting a barely discernible object in an additive Gaussian background clutter using a single pixel in a sequence of digital images. In contrast to this detector designed for the subpixel object, we developed a generalized likelihood ratio approach to the detection of a multipixel object of unknown shape, size, and position in an additive signal-dependent Gaussian background and noise. The proposed detector modifies the MSD by adding the additional term proportional to the square of the difference between the background variances under two statistical hypotheses. The performances of these detectors are evaluated for the example scenario of two multipixel floating objects on the agitated sea surface. The crucial characteristic of the proposed detector is that prior knowledge of the target size, shape, and position is not required. Computer simulation and experimental results have shown that the proposed detector outperforms the MSD, especially in the case of weak and poorly contrasted objects of unknown shape, size, and position.

Paper Details

Date Published: 26 January 2016
PDF: 11 pages
J. Appl. Remote Sens. 10(1) 015006 doi: 10.1117/1.JRS.10.015006
Published in: Journal of Applied Remote Sensing Volume 10, Issue 1
Show Author Affiliations
Victor Golikov, Univ. Autónoma del Carmen (Mexico)
Marco Rodriguez-Blanco, Univ. Autónoma del Carmen (Mexico)
Olga Lebedeva, Univ. Autónoma del Carmen (Mexico)

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