Abstract

GAONA BARRERA, Andrés Eduardo; LUGO CURREA, Néstor Andrés  and  ROLDAN HERNANDEZ, Alvaro Fernando. Study of two neural feed-forward structures for digital image compression. Rev.fac.ing.univ. Antioquia [online]. 2012, n.65, pp.85-98. ISSN 0120-6230.

This paper shows and explains the process implemented for the development of feed-forward neural networks with the aim of compress digital image color. It sets out some traditional techniques and develops two topologies to implement feed forward. During the development of networks, the items that are considered: number of layers, number of neurons, image type, size and number of blocks to train, to optimize performance during final training. It also discusses the standard quality of the image obtained, as peak signal noise relation (PSNR) and compression, which typically obtain values above 35dB in terms of PSNR and 2 bits per pixel in gray or 3 bpp color images, with maximum time of 3 seconds for images less than 1 mega pixel. Finally out some drawbacks and presents conclusions of this type of compression.

Keywords : Compression rate; digital image compression; lossy compression; feedforward neural networks; peak signal noise relation.

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