Removing Parallax-Induced Changes in Hyperspectral Change Detection

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Conference Proceeding

Publication Date



Hyperspectral-based change detection is often inadvertently affected by image artifacts, reducing the accuracy of the change detector. We present a Hyperspectral Change Detection (HSCD) process to distinguish parallax-induced change from legitimate change. Image parallax decreases the accuracy of change detection results. The approach introduced in this paper utilizes a combination of a spectral change detector and stereo geometry to reduce parallax-induced false alarms. Image parallax is determined by considering the error in the epipolar constraint, meaning the corresponding points between two images must lie on epipolar lines. Experimental analysis shows a false alarm reduction by nearly one order of magnitude on synthetic hyperspectral imagery and nearly two orders of magnitude on real hyperspectral imagery. Abstract © 2012 IEEE.

Source Publication

IEEE International Geoscience and Remote Sensing Symposium, 2012

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