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Proceedings Paper

A method for improved localization of edges in multi/hyperspectral imagery
Author(s): Sreenath Rao Vantaram; Eli Saber
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Paper Abstract

We propose an efficient approach for achieving improved localization of edges detected in remotely sensed imagery wherein the improvement is in the localization of the detected edges. This work is based on the notion that the partial derivatives of individual image components used for vector gradient computation often yields thick edges, and consequently optimizing them to only constitute contributions towards their local scalar gradient maxima before being employed in a vector field gradient calculation can yield significantly localized edges in the final edge map. Our approach was tested on several remotely sensed multispectral and hyperspectral datasets with favorable results.

Paper Details

Date Published: 24 September 2011
PDF: 6 pages
Proc. SPIE 8135, Applications of Digital Image Processing XXXIV, 81351L (24 September 2011); doi: 10.1117/12.893919
Show Author Affiliations
Sreenath Rao Vantaram, Rochester Institute of Technology (United States)
Eli Saber, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 8135:
Applications of Digital Image Processing XXXIV
Andrew G. Tescher, Editor(s)

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