Change Detection in Optical Remote Sensing Images Using Difference-Based Methods and Spatial Information

Rouhollah Dianat

doi:10.1109/LGRS.2009.2031686

2010-01-01

PRE

Rouhollah Dianat *

Shohreh Kasaei

DOI：10.1109/LGRS.2009.2031686

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摘要

En 中文

A new and general framework-called modified polynomial regression (MPR)-is introduced in this letter, which detects the changes that occurred in remote sensing images. It is an improvement of the conventional polynomial regression (CPR) method. Most change detection (CD) methods, including CPR, do not consider the spatial relations among image pixels. To improve CPR, our proposed framework incorporates the spatial information into the CD process by using linear spatial-oriented image operators. It is proved that MPR preserves the affine invariance property of CPR. A realization of MPR is proposed, which employs the image derivatives to account for spatiality. Experimental results show the superiority of the proposed method over the CPR method and three other difference-based CD methods, namely, simple differencing, linear chronochrome CD, and multivariate alteration detection.

Keyword:

Pattern recognition

remote sensing