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Proceedings Paper

Resolution enchancement of thermal infrared images via high-resolution class-map and statistical methods
Author(s): David Schlingmeier; John R. Schott
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Paper Abstract

Work has been on-going at the Rochester Institute of Technology's Center for Imaging Science in the spatial resolution enhancement ofthermal infrared imagery. Based upon the most recent work by the Digital Imaging and Remote Sensing group, several areas of study were carried out using M7 and Landsat data sets. All investigations undertaken were confmed to cases that ensure radiometric fidelity across image processing operations, since derivation of accurate temperature or emissivity maps necessitate this requirement. Given a low spatial resolution thermal band, these methods produced a high resolution estimate thereofbased on enhancement using: (1) a single panchromatic band; and (2) a high resolution class-map derived from multi-spectral bands. The single band method relies on thresholding of grey-levels within a local window. Local processing is also the key to the class-map, multi-band approach. A variety of factors related to output quality, such as resolution ratio and the number of local windows, were examined. M7 scenes were used to develop/test the algorithm by degrading thermal data and restoring it to the original resolution. The completed algorithms have also been applied to Landsat imagery with the reflective channels used to enhance the 120 m thermal band. An overview ofthe background equations is given, workings ofthe algorithm are presented and resulting output is shown and compared to truth.

Paper Details

Date Published: 2 July 1998
PDF: 12 pages
Proc. SPIE 3372, Algorithms for Multispectral and Hyperspectral Imagery IV, (2 July 1998); doi: 10.1117/12.312612
Show Author Affiliations
David Schlingmeier, Department of National Defence (Canada)
John R. Schott, Rochester Institute of Technology (United States)

Published in SPIE Proceedings Vol. 3372:
Algorithms for Multispectral and Hyperspectral Imagery IV
Sylvia S. Shen; Michael R. Descour, Editor(s)

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