Conference paper
Self-organized color image quantization for color image data compression
IEEE International Conference on Neural Networks, pp.1622-1626
IEEE
IEEE International Conference on Neural Networks (San Francisco, CA; USA, 28/03/1993–01/04/1993)
1993
Abstract
A neural network approach to image color quantization and hence to image data compression is presented. Self-organizing feature maps form a basis for general vector quantization, and this is applied to the tristimulus color values of image pixels. For image telecommunication systems such as videoconferencing, it is desirable to constrain the encoder to a single pass of the image using the normal raster scan. This conflicts with the training requirements of a self-organized network. By the appropriate choice of codebook size this limitation can be turned into an advantage. The network performs a mix of vector quantization and run-length coding, thus compressing the image data in two ways
Details
- Title
- Self-organized color image quantization for color image data compression
- Authors/Creators
- K.R.L. Godfrey (Author/Creator)Y. Attikiouzel (Author/Creator) - The University of Western Australia
- Publication Details
- IEEE International Conference on Neural Networks, pp.1622-1626
- Conference
- IEEE International Conference on Neural Networks (San Francisco, CA; USA, 28/03/1993–01/04/1993)
- Publisher
- IEEE
- Identifiers
- 991005540842007891
- Copyright
- © 1993 IEEE
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
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