Effects of compression on the classification of hyperspectral images

Authors:
Euisun Choi;Sangwook Lee;Chulhee Lee
Affiliations:
Dept. Electrical and Electronic Eng., Yonsei Univ., Seoul, South Korea;Dept. Electrical and Electronic Eng., Yonsei Univ., Seoul, South Korea;Dept. Electrical and Electronic Eng., Yonsei Univ., Seoul, South Korea
Venue:
ICS'08 Proceedings of the 12th WSEAS international conference on Systems
Year:
2008

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Abstract

In this paper, we investigate the effects of compression on the classification of hyperspectral images. It has been reported reconstructed images after compression often increase classification accuracy. In this paper, by using various experiments and analyses, we examine the causes and implications of this phenomenon. In particular, we used the three dimensional version of the set partitioning in hierarchical trees (SPIHT) algorithm as a compression method. We compared the classification accuracies in the original images and the reconstructed images at various bit rates. The experimental results and analyses indicated that higher classification accuracy did not necessarily mean improved performance since the classification results might differ from those of original data.