1 September 1990 Multiscale image coding using the Kohonen neural network
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Proceedings Volume 1360, Visual Communications and Image Processing '90: Fifth in a Series; (1990) https://doi.org/10.1117/12.24101
Event: Visual Communications and Image Processing '90, 1990, Lausanne, Switzerland
Abstract
This paper proposes a new method for image coding involving two steps. First, we use a 'Dual Recursive Wavelet' Transform in order to obtain a set of subclasses of images with better characteristics than the original image (lower entropy, edges discrimination, ... ). Second, according to Shannon's rate distortion theory, the wavelet coefficients are vector quantized using the Kohonen Self-Organizing Feature Maps. We compare this training method with the well known LBG algorithm.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Marc Antonini, Marc Antonini, Michel Barlaud, Michel Barlaud, Pierre Mathieu, Pierre Mathieu, J. C. Feauveau, J. C. Feauveau, } "Multiscale image coding using the Kohonen neural network", Proc. SPIE 1360, Visual Communications and Image Processing '90: Fifth in a Series, (1 September 1990); doi: 10.1117/12.24101; https://doi.org/10.1117/12.24101
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