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Antonio Alarcón-Paredes, Amadeo-José Argüelles-Cruz, Oleksiy Pogrebnyak
Computacion y Sistemas Volume 17, Issue 4, 2013, Pages 527-541
Publication year: 2013

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In this paper, a new method of alphabeta associative memories for images (MAABI) is presented. This method results in the alphabeta transform (TAB) for images. The alphabeta transform presented in this paper is applied to subblocks of a grayscale image and generates an alphabeta heteroassociative memory on each subblock using a given transformation matrix. By means of the inverse alphabeta transform (TABI), the original image patterns are recovered. The data compression process is divided into three stages: transformation, quantization and coding. Our model is focused on image transformation; we compare it with the morphological transform (TM) based on the morphological associative memories (MAM). In order to measure the number of bits contained in an image, the Shannon’s entropy is used. The TM, as well as such traditional transforming methods as the discrete cosine transform (DCT) and the discrete wavelet transform (DWT), cannot perform compression over an image; that is why the main advantage of the AB is a smaller value of the entropy measure of the transformed image compared to the entropy of the original image. In addition, TAB provides a faster processing with a small number of elementary operations such as addition, subtraction, maximum and minimum.

Author keywords

Associative memories, Compression, Image processing, Pattern recognition, Transform methods

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