Title :
Directional segmented matched filter for hyperspectral images
Author_Institution :
Grad. Stat. Dept., Rochester Inst. of Technol., Rochester, NY, USA
Abstract :
We propose a new type of a segmented matched filter, called a directional segmented matched filter (DSMF), based on geometric considerations between the target, background, and a given pixel. We use a modified k-means segmentation algorithm that has produced the background suitable for our detectors. We demonstrate numerical results on the performance of two versions of DSMF on two different targets. The two versions perform very differently, apparently depending on the type of target and the background structure.
Keywords :
geophysical image processing; image segmentation; matched filters; object detection; DSMF; directional segmented matched filter; hyperspectral images; k-means segmentation algorithm; Clustering algorithms; Covariance matrix; Detectors; Hyperspectral imaging; Image segmentation; Matched filters; hyperspectral images; matched filter; segmentation; target detection;
Conference_Titel :
Hyperspectral Image and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2011 3rd Workshop on
Conference_Location :
Lisbon
Print_ISBN :
978-1-4577-2202-8
DOI :
10.1109/WHISPERS.2011.6080911