Title :
Image compression using topological maps and MLP
Author :
Burel, Gilles ; Catros, Jean-Yves
Author_Institution :
Thomson CSF, Cesson-Sevigne, France
Abstract :
An image compression technique is proposed in which a multilayer perceptron (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
Keywords :
feedforward neural nets; image coding; image processing; topology; vector quantisation; Kohonen algorithm; code-book; image coding; image compression; image processing; multilayer perceptron; topological maps; vector quantization; Backpropagation; Bandwidth; Bit rate; Books; Decoding; Image coding; Image storage; Multilayer perceptrons; Transform coding; Vector quantization;
Conference_Titel :
Neural Networks, 1993., IEEE International Conference on
Conference_Location :
San Francisco, CA
Print_ISBN :
0-7803-0999-5
DOI :
10.1109/ICNN.1993.298645