Active contours with edges: combining hyperspectral and grayscale segmentation

Alex Chen

doi:10.1117/12.974445

8 November 2012 Active contours with edges: combining hyperspectral and grayscale segmentation

Alex Chen

Proceedings Volume 8537, Image and Signal Processing for Remote Sensing XVIII; 85370B (2012) https://doi.org/10.1117/12.974445
Event: SPIE Remote Sensing, 2012, Edinburgh, United Kingdom

Abstract

In this work, we introduce a method to segment hyperspectral images using a Chan-Vese framework. We utilize a modified l2 distance especially well-suited for hyperspectral classification problems. This distance considers spectral signal shape rather than illumination for the classification of objects. The practicality of multiple phase segmentation in this application is also demonstrated. We then use a high spatial resolution grayscale or color image and a high spectral, but low spatial resolution hyperspectral image to produce a fused segmentation result that is more accurate than segmentation on either image alone. Lastly, we show that the algorithm also gives a natural method for end member selection and apply this result to anomaly detection.

Citation Download Citation

Alex Chen "Active contours with edges: combining hyperspectral and grayscale segmentation", Proc. SPIE 8537, Image and Signal Processing for Remote Sensing XVIII, 85370B (8 November 2012); https://doi.org/10.1117/12.974445

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