Morphological Transform for Image Compression. (21st May 2008)

• Record Type: Journal Article
• Authors: Guzmán Guzmán, Enrique Enrique; Pogrebnyak Pogrebnyak, Oleksiy Oleksiy; Yañez Yañez, Cornelio Cornelio; Sanchez Fernandez Sanchez Fernandez, Luis Pastor Luis Pastor
• Other Names: Lefèvre Lefèvre Sébastien Sébastien Academic Editor.
• Is Part Of: EURASIP journal on advances in signal processing. Volume 2008(2008)
• Publication Date: 2008-05-21
• Subjects: Signal processing -- Periodicals; Traitement du signal; Signal processing; Periodicals; 621.3822
• DOI: 10.1155/2008/426580
• Languages: English
• ISSNs: 1687-6172

Abstract

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. TheMT 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 theMT is the processing speed, whereas the compression rate and the signal-to-noise ratio are competitive to conventional transforms.