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Grayscale Images and RGB Video: Compression by Morphological Neural Network

  • Osvaldo de Souza
  • Paulo César Cortez
  • Francisco A. T. F. da Silva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7477)

Abstract

This paper investigates image and RGB video compression by a supervised morphological neural network. This network was originally designed to compress grayscale image and was then extended to RGB video. It supports two kinds of thresholds: a pixel-component threshold and pixel-error counting threshold. The activation function is based on an adaptive morphological neuron, which produces suitable compression rates even when working with three color channels simultaneously. Both intra-frame and inter-frame compression approaches are implemented. The PSNR level indicates that the compressed video is compliant with the desired quality levels. Our results are compared to those obtained with commonly used image and video compression methods. Network application results are presented for grayscale images and RGB video with a 352 × 288 pixel size.

Keywords

Supervised Morphological Neural Network RGB Video Compression Image Compression 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Osvaldo de Souza
    • 1
  • Paulo César Cortez
    • 1
  • Francisco A. T. F. da Silva
    • 2
  1. 1.DETIFederal University of CearáFortalezaBrazil
  2. 2.National Institute For Space ResearchROENEusébioBrazil

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