Classification Consistency Of Bandwidth Compressed Multispectral Scanned (MSS) Images Using Bayes Supervised Classifier

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.