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Proceedings Paper

Classification Consistency Of Bandwidth Compressed Multispectral Scanned (MSS) Images Using Bayes Supervised Classifier
Author(s): A. Habibi; A. Y. Hung
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Paper Abstract

For many pattern classification and pattern recognition applications, the multispectral data is first used to obtain a classified image (map). This image is then used for different image data extraction and classifi-cation applications. It is important that a particular bandwidth compression method should not result in significant changes in the resulting classification map. In this article the performance of a hybrid encoder (Hadamard/DPCM) in retaining the classification accuracy of the classified image is evaluated. It is shown that using a Bayes supervised classifier the classification accuracy of the bandwidth compressed picture is actually higher than the original picture.

Paper Details

Date Published: 8 December 1977
PDF: 6 pages
Proc. SPIE 0119, Applications of Digital Image Processing, (8 December 1977); doi: 10.1117/12.955699
Show Author Affiliations
A. Habibi, TRW Defense and Space Systems Group (United States)
A. Y. Hung, TRW Defense and Space Systems Group (United States)


Published in SPIE Proceedings Vol. 0119:
Applications of Digital Image Processing
Andrew G. Tescher, Editor(s)

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