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Image compression using topological maps and MLP

Abstract : Image compression is an essential task for image storage and transmission. We propose a compression technique in which an MLP predictor takes advantage of the topological properties of the Kohonen algorithm. The Kohonen algorithm creates a code-book which is used for Vector Quantization of the source image. Then,an MLP is trained to predict references to code-book, allowing further compression. Even with difficult images, the result is a reduction of 15% to 20% of the bit rate compared with classical Vector Quantization techniques, for the same quality of decoded images.
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Contributor : Gilles Burel Connect in order to contact the contributor
Submitted on : Sunday, May 9, 2021 - 8:03:32 PM
Last modification on : Thursday, May 13, 2021 - 8:33:58 PM


  • HAL Id : hal-03221764, version 1



Gilles Burel, Jean-Yves Catros. Image compression using topological maps and MLP. IEEE Int. Conf. on Neural Networks, Mar 1993, San Francisco, United States. pp.727-731. ⟨hal-03221764⟩



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