Paper
1 June 2001 Mutual information as a similarity measure for remote sensing image registration
Author Affiliations +
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kisha Johnson, Arlene Cole-Rhodes, Ilya Zavorin, and Jacqueline Le Moigne "Mutual information as a similarity measure for remote sensing image registration", Proc. SPIE 4383, Geo-Spatial Image and Data Exploitation II, (1 June 2001); https://doi.org/10.1117/12.428251
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CITATIONS
Cited by 29 scholarly publications.
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KEYWORDS
Image registration

Wavelets

Remote sensing

Image processing

Medical imaging

Earth observing sensors

Feature extraction

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