NDLI: Optimally adaptive transform coding

Content Provider	IEEE Xplore Digital Library
Author	Dony, R.D. Haykin, S.
Copyright Year	1992
Abstract	The optimal linear block transform for coding images is well known to be the Karhunen-Loeve transformation (KLT). However, the assumption of stationarity in the optimality condition is far from valid for images. Images are composed of regions whose local statistics may vary widely across an image. While the use of adaptation can result in improved performance, there has been little investigation into the optimality of the criterion upon which the adaptation is based. In this paper we propose a new transform coding method in which the adaptation is optimal. The system is modular, consisting of a number of modules corresponding to different classes of the input data. Each module consists of a linear transformation, whose bases are calculated during an initial training period. The appropriate class for a given input vector is determined by the subspace classifier. The performance of the resulting adaptive system is shown to be superior to that of the optimal nonadaptive linear transformation. This method can also be used as a segmentor. The segmentation it performs is independent of variations in illumination. In addition, the resulting class representations are analogous to the arrangement of the directionally sensitive columns in the visual cortex.<>
Sponsorship	IEEE Signal Processing Society
Starting Page	1358
Ending Page	1370
Page Count	13
File Size	1772953
File Format	PDF
ISSN	10577149
Volume Number	4
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1995-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Transform coding Image coding Statistics Image segmentation Karhunen-Loeve transforms Neural networks Pulse modulation Vectors Adaptive systems Lighting
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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