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Proceedings Paper

Image compression using multiresolution morphological decomposition
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Paper Abstract

Multiresolution image decomposition based on nonlinear filtering has received a lot of attention recently. In this research, we investigate the coding issue for one class of nonlinear multiresolution image decomposition based on mathematical morphology. We consider the use of opening and closing operations with a flat structure element to achieve image decomposition. The entropy and histogram of the difference images in the image pyramid are then examined. We give a numerical example to demonstrate potential advantages of the morphological filtering approach over the conventional linear filtering approach in the context of image coding. However, we also point out difficulties encountered in our study that have to be overcome before the method can be practically used.

Paper Details

Date Published: 30 June 1994
PDF: 12 pages
Proc. SPIE 2300, Image Algebra and Morphological Image Processing V, (30 June 1994); doi: 10.1117/12.179214
Show Author Affiliations
Ching-Han Lance Hsu, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)

Published in SPIE Proceedings Vol. 2300:
Image Algebra and Morphological Image Processing V
Edward R. Dougherty; Paul D. Gader; Michel Schmitt, Editor(s)

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