Title :
Classification consistency for bandwidth compressed multispectral imagery
Author :
Habibi, Ali ; Blyth, Barbara ; Andrews, Carl
Author_Institution :
Aerosp. Corp., El Segundo, CA, USA
Abstract :
With the recent surge of interest in machine processing of multispectral imagery for recognition and change detection, the impact of bandwidth compression on the consistency of machine classification is becoming more significant. In this article we evaluate the impact of bandwidth compression on the classification consistency of machine classifiers. The emphasis is on the performance of one-dimensional DPCM and Bayesian classifiers, although we have compared the results with a number of other bandwidth compression techniques, such as the two-dimensional DPCM and the VQ based techniques. Additionally, the effect of the channel error on the classification consistency of the DPCM system is evaluated
Keywords :
Bayes methods; bandwidth compression; image coding; image recognition; pulse-code modulation; bandwidth compressed multispectral imagery; bandwidth compression; change detection; channel error; classification consistency; image recognition; machine classification; machine classifiers; machine processing; one-dimensional Bayesian classifiers; one-dimensional DPCM classifiers; Application software; Bandwidth; Bayesian methods; Distortion measurement; Earth; Image coding; Image recognition; Multispectral imaging; Propagation losses; Pulse modulation; Robustness; Speech; Surges;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342321