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Proceedings Paper

Image compression algorithm using local edge information
Author(s): Ahmed El-Mabrouk; Amar Aggoun
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Paper Abstract

An algorithm for image compression, based on local histogram analysis, is presented. A given image is compressed by dividing the image into nonoverlapping square blocks and coding the edge information in each block. The edge information is extracted by first differentiating the original image, quantizing the differential image, then investigated the local histogram of small blocks of the differential image. Depending on the behavior of the local histograms in the differential image, the corresponding blocks in the original image are classified into visually active and visually continuous blocks. The visually continuous blocks are coded using the mean value only. A visually active block is coded using the location and orientation of the edge within the block. As a result, the compression ratio of the proposed algorithm depends on the behavior of the local histogram, which in turn depends heavily on the quantization process of the differential image. In this paper, the effect of the quantization of the differential image on the compression ratio and the image quality is discussed.

Paper Details

Date Published: 10 January 1997
PDF: 9 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263259
Show Author Affiliations
Ahmed El-Mabrouk, De Montfort Univ./Leicester (United Kingdom)
Amar Aggoun, De Montfort Univ./Leicester (United Kingdom)


Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp, Editor(s)

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