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Proceedings Paper

Mutual information as a similarity measure for remote sensing image registration
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Paper Abstract

Feature-based matching is essential for attaining sub-pixel registration of remotely sensed imagery. In this work, we focus on two different similarity metrics which are used to match extracted features, correlation and mutual information. Although mutual information has been successfully applied to medical image registration, these metrics have not been systematically studied for remote sensing applications. This paper presents some first results in the comparison of correlation and mutual information, relative to their respective accuracy and response to noise. The study is performed using Landsat-TM data.

Paper Details

Date Published: 1 June 2001
PDF: 11 pages
Proc. SPIE 4383, Geo-Spatial Image and Data Exploitation II, (1 June 2001); doi: 10.1117/12.428251
Show Author Affiliations
Kisha Johnson, Morgan State Univ. (United States)
Arlene Cole-Rhodes, Morgan State Univ. (United States)
Ilya Zavorin, Univ. of Maryland/College Park and NASA Goddard Space Flight Ctr. (United States)
Jacqueline Le Moigne, NASA Goddard Space Flight Ctr. (United States)

Published in SPIE Proceedings Vol. 4383:
Geo-Spatial Image and Data Exploitation II
William E. Roper, Editor(s)

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