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Design of an Evolutionary Codebook Based on Morphological Associative Memories

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MICAI 2007: Advances in Artificial Intelligence (MICAI 2007)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4827))

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Abstract

A central issue in the use of vector quantization (VQ) for speech or image compression is the specification of the codebook. In this paper, the design of an evolutionary codebook based on morphological associative memories (MAM) is presented. The algorithm proposed for codebook generation involves two steps. First, having a set of images, one of the images is chosen to create the initial codebook. The algorithm applied to the image for codebook generation uses the morphological autoassociative memories (MAAM). Second, an evolution process of codebook creation occurs applying the algorithm on new images. This process adds the information codified of the next image to the codebook allowing to recover the images with better quality without affecting the processing speed. The performance of the generated codebook is analyzed in case when MAAM in both max and min categories are used. The presented algorithm was applied to image set after discrete cosine transformation followed by a quantization process. The proposed algorithm has a high processing speed and provides a notable improvement in signal to noise ratio.

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Authors and Affiliations

  1. Universidad Tecnológica de la Mixteca,  

    Enrique Guzmán

  2. Centro de Investigación en Computación del Instituto Politécnico Nacional,  

    Oleksiy Pogrebnyak & Cornelio Yañez

Authors
  1. Enrique Guzmán
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  2. Oleksiy Pogrebnyak
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  3. Cornelio Yañez
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Alexander Gelbukh Ángel Fernando Kuri Morales

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© 2007 Springer-Verlag Berlin Heidelberg

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Guzmán, E., Pogrebnyak, O., Yañez, C. (2007). Design of an Evolutionary Codebook Based on Morphological Associative Memories. In: Gelbukh, A., Kuri Morales, Á.F. (eds) MICAI 2007: Advances in Artificial Intelligence. MICAI 2007. Lecture Notes in Computer Science(), vol 4827. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76631-5_57

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  • DOI: https://doi.org/10.1007/978-3-540-76631-5_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76630-8

  • Online ISBN: 978-3-540-76631-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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