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Image Enhancement by High-Order Gaussian Derivative Filters Simulating Non-classical Receptive Fields in the Human Visual System

  • Kuntal Ghosh
  • Sandip Sarkar
  • Kamales Bhaumik
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3776)

Abstract

The non-linearity exhibited by the non-classical receptive field in human visual system has been combined with the linear classical receptive field model. This enables us to construct higher order Gaussian Derivatives as a linear combination of lower order derivatives at different scales. Based on this, a new kernel which simulates non-classical receptive fields with extended disinhibitory surrounds, has been proposed. It is easy to implement and finds justification from an old psychophysical angle too. The proposed kernel has been shown to perform better than the well-known Laplacian kernel, which models the classical excitatory-inhibitory receptive fields.

Keywords

Human Visual System Image Enhancement Lower Order Derivative Fourth Order Derivative Laplacian Kernel 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Kuntal Ghosh
    • 1
  • Sandip Sarkar
    • 1
  • Kamales Bhaumik
    • 1
  1. 1.Microelectronics DivisionSaha Institute of Nuclear PhysicsKolkataIndia

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