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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Paskaleva, B.S. Hayat, M.M. Woo-Yong Jang Sharma, Y.D. Bender, S.C. Krishna, S. |
| Copyright Year | 2010 |
| Description | Author affiliation: Los Alamos National Laboratory, NM 87545, USA (Bender, S.C.) || Sandia National Laborotories, Albuquerque, NM 87123, USA (Paskaleva, B.S.) || ECE Department and Center for High Technology Materials, University of New Mexico, Albuquerque, 87131, USA (Hayat, M.M.; Woo-Yong Jang; Sharma, Y.D.; Krishna, S.) |
| Abstract | Image segmentation is one of the most important and difficult tasks in digital image processing. It represents a key stage of automated image analysis and interpretation. Segmentation algorithms for gray-scale images utilize basic properties of intensity values such as discontinuity and similarity. However, it is possible to enhance edge-detection capability by means of using spectral information provided by multispectral (MS) or hyperspectral (HS) imagery. In this paper we consider image segmentation algorithms for multispectral images with particular emphasis on detection of multi-color or multispectral edges. More specifically, we report on an algorithm for joint spatio-spectral (JSS) edge detection. By joint we mean simultaneous utilization of spatial and spectral characteristics of a given MS or HS image. The JSSbased edge-detection approach, termed Spectral Ratio Contrast (SRC) edge-detection algorithm, utilizes the novel concept of matching edge signatures. The edge signature represents a combination of spectral ratios calculated using bands that enhance the spectral contrast between the two materials. In conjunction with a spatial mask, the edge signature give rise to a multispectral operator that can be viewed as a threedimensional extension of the mask. In the extended mask, the third (spectral) dimension of each hyper-pixel can be chosen independently. The SRC is verified using MS and HS imagery from a quantum-dot in a well infrared (IR) focal plane array, and the Airborne Hyperspectral Imager. |
| Starting Page | 2198 |
| Ending Page | 2201 |
| File Size | 209012 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424495658 |
| ISSN | 21537003 |
| e-ISBN | 9781424495665 |
| e-ISBN | 9781424495641 |
| DOI | 10.1109/IGARSS.2010.5648869 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-07-25 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image edge detection Materials Gray-scale Image segmentation Joints Image color analysis Detectors iso-luminant Edge detection multispectral |
| Content Type | Text |
| Resource Type | Article |
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