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Journal of Applied Remote Sensing

Change detection in remote sensing images using modified polynomial regression and spatial multivariate alteration detection
Author(s): Rouhollah Dianat; Shohreh Kasaei
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Paper Abstract

A new and efficient method for incorporating the spatiality into difference-based change detection (CD) algorithms is introduced in this paper. It uses the spatial derivatives of image pixels to extract spatial relations among them. Based on this methodology, the performances of two famous difference-based CD methods, conventional polynomial regression (CPR) and multivariate alteration detection (MAD), are improved and called modified polynomial regression (MPR) and spatial multivariate alteration detection (SMAD), respectively. Various quantitative and qualitative evaluations have shown the superiority of MPR over CPR and SMAD over MAD. Also, the superiority of SMAD over all mentioned CD algorithms is shown. Moreover, it has been proved that both proposed methods enjoy the affine invariance property.

Paper Details

Date Published: 1 November 2009
PDF: 12 pages
J. Appl. Remote Sens. 3(1) 033561 doi: 10.1117/1.3269611
Published in: Journal of Applied Remote Sensing Volume 3, Issue 1
Show Author Affiliations
Rouhollah Dianat, Sharif Univ. of Technology (Iran, Islamic Republic of)
Shohreh Kasaei, Sharif Univ. of Technology (Iran, Islamic Republic of)


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