8 December 1977 Classification Consistency Of Bandwidth Compressed Multispectral Scanned (MSS) Images Using Bayes Supervised Classifier
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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.
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A. Habibi, A. Habibi, A. Y. Hung, A. Y. Hung, } "Classification Consistency Of Bandwidth Compressed Multispectral Scanned (MSS) Images Using Bayes Supervised Classifier", Proc. SPIE 0119, Applications of Digital Image Processing, (8 December 1977); doi: 10.1117/12.955699; https://doi.org/10.1117/12.955699
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