Rank order polynomial decomposition for image compression

被引：0

作者：

Egger, O ^{[1
]}

Gruter, R ^{[1
]}

Vesin, JM ^{[1
]}

Kunt, M ^{[1
]}

机构：

[1] LCAV, Audio Visual Commun Lab, CH-1015 Lausanne, Switzerland

来源：

PROCEEDINGS OF THE 1998 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-6 | 1998年

关键词：

D O I：

暂无

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

In this paper, a novel decomposition scheme for image compression is presented. It is capable to apply any nonlinear model to compress images in a.lossless way. Here, a very efficient polynomial model that considers spatial information as well as order statistic information is introduced. This new rank order polynomial decomposition (ROPD) that allows also for a progressive bitstream is applied to various images of different nature and compared to the morphological subband decomposition (MSD) and to the best prediction mode for lossless compression of the international standard JPEG. For all compressed images, ROPD provides better compression results than MSD and clearly outperforms the lossless mode of JPEG.

引用

页码：2641 / 2644

页数：4

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