A Bio-Inspired Image Coder with Temporal Scalability

  • Khaled Masmoudi
  • Marc Antonini
  • Pierre Kornprobst
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6915)

Abstract

We present a novel bio-inspired and dynamic coding scheme for static images. Our coder aims at reproducing the main steps of the visual stimulus processing in the mammalian retina taking into account its time behavior. The main novelty of this work is to show how to exploit the time behavior of the retina cells to ensure, in a simple way, scalability and bit allocation. To do so, our main source of inspiration will be the biologically plausible retina model called Virtual Retina. Following a similar structure, our model has two stages. The first stage is an image transform which is performed by the outer layers in the retina. Here it is modelled by filtering the image with a bank of difference of Gaussians with time-delays. The second stage is a time-dependent analog-to-digital conversion which is performed by the inner layers in the retina. Thanks to its conception, our coder enables scalability and bit allocation across time. Also, our decoded images do not show annoying artefacts such as ringing and block effects. As a whole, this article shows how to capture the main properties of a biological system, here the retina, in order to design a new efficient coder.

Keywords

Static image compression bio-inspired signal coding retina 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Khaled Masmoudi
    • 1
  • Marc Antonini
    • 1
  • Pierre Kornprobst
    • 2
  1. 1.I3S laboratoryUNS–CNRSSophia-AntipolisFrance
  2. 2.NeuroMathComp Team ProjectINRIASophia-AntipolisFrance

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