The region-based description of multispectral images enables important high-level tasks such as data mining and retrieval, and region-of-interest selection. In order to obtain an efficient representation of such images we resort to adaptive transform coding techniques. Such techniques, however, require a considerable information overhead, which must be carefully managed to obtain a satisfactory rate-distortion performance. In this work we develop several region-based coding schemes and compare them with conventional (non-adaptive) and class-based schemes, so as to single out the rate-distortion gains/losses of this approach. ©2006 IEEE.

Adaptive region-based compression of multispectral images

Cagnazzo M.
;
2006

Abstract

The region-based description of multispectral images enables important high-level tasks such as data mining and retrieval, and region-of-interest selection. In order to obtain an efficient representation of such images we resort to adaptive transform coding techniques. Such techniques, however, require a considerable information overhead, which must be carefully managed to obtain a satisfactory rate-distortion performance. In this work we develop several region-based coding schemes and compare them with conventional (non-adaptive) and class-based schemes, so as to single out the rate-distortion gains/losses of this approach. ©2006 IEEE.
2006
Proceedings - International Conference on Image Processing, ICIP
1-4244-0480-0
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3469806
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