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  • Research Article
  • Open Access

Morphological Transform for Image Compression

  • 1,
  • 2Email author,
  • 2 and
  • 2
EURASIP Journal on Advances in Signal Processing20082008:426580

https://doi.org/10.1155/2008/426580

Received: 29 August 2007

Accepted: 4 April 2008

Published: 20 April 2008

Abstract

A new method for image compression based on morphological associative memories (MAMs) is presented. We used the MAM to implement a new image transform and applied it at the transformation stage of image coding, thereby replacing such traditional methods as the discrete cosine transform or the discrete wavelet transform. Autoassociative and heteroassociative MAMs can be considered as a subclass of morphological neural networks. The morphological transform (MT) presented in this paper generates heteroassociative MAMs derived from image subblocks. The MT is applied to individual blocks of the image using some transformation matrix as an input pattern. Depending on this matrix, the image takes a morphological representation, which is used to perform the data compression at the next stages. With respect to traditional methods, the main advantage offered by the MT is the processing speed, whereas the compression rate and the signal-to-noise ratio are competitive to conventional transforms.

Keywords

  • Traditional Method
  • Quantum Information
  • Processing Speed
  • Transformation Matrix
  • Discrete Wavelet

Publisher note

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Authors’ Affiliations

(1)
Universidad Tecnológica de la Mixteca, Huajauapan de León, Mexico
(2)
Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico

Copyright

© Enrique Guzmán et al. 2008

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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