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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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
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