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Proceedings Paper

A new nonlinear change detection approach based on band ratioing
Author(s): Bulent Ayhan; Chiman Kwan; Jin Zhou
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Paper Abstract

Change detection using hyperspectral images is important in surveillance and reconnaissance operations. The process involves two images: one reference and one test. Many algorithms such as chronochrome (CC) and covariance equalization (CE) were proposed in the past. In this paper, we will present a new nonlinear change detection framework for hyperspectral images. The idea was motivated by the band rationing concept. First, image segmentation is applied to the reference image. For each segmented subimage in the reference image, the bands with the most and least variations are found. Then new images are formed by dividing the two bands. Similarly, the new band ratioed images are formed in the test images. Second, we propose to apply CC or CE to generate residual images. Finally, anomaly detection algorithms are applied to detect changes. Actual hyperspectral images have been used in our studies. Receiver operating characteristics (ROC) curves were used to compare the various options. Results showed that this approach can achieve excellent detection performance.

Paper Details

Date Published: 8 May 2018
PDF: 10 pages
Proc. SPIE 10644, Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV, 1064410 (8 May 2018); doi: 10.1117/12.2303648
Show Author Affiliations
Bulent Ayhan, Signal Processing, Inc. (United States)
Chiman Kwan, Signal Processing, Inc. (United States)
Jin Zhou, Signal Processing, Inc. (United States)

Published in SPIE Proceedings Vol. 10644:
Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery XXIV
Miguel Velez-Reyes; David W. Messinger, Editor(s)

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