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id ijac20032201
authors Mahalingam, Ganapathy; Kavasseri, Rajesh G.
year 2004
title Improving Objective Digital Images with Neuronal Processing: A Computational Approach
source International Journal of Architectural Computing vol. 2 - no. 2
summary This paper describes an experiment where an imagerecorded with a digital camera is processed using anelectro-physiological model of a neuron. Theluminosity level of each pixel of the source image istreated as the stimulus for an individual neuron, andthe source image is transformed into a responseimage based on the processing behavior of theHodgkin-Huxley neuronal model. It is seen thattransformation of the image through neuronalprocessing yields (i) more evenly balanced levels ofluminosity and (ii) a more ‘subjective’ rendering of theenvironment than what was photographed with thedigital camera.The CCD (charge coupled device) –based digital camera reveals its limitation as a linearrecording device that does not have a balanceddynamic range.The neuronal processing of the imageadds non-linearity and a balanced range to theluminosity levels in the image, rendering it closer to a‘subjective’ perception of the scene.
series journal
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100%; open Rinzel, J. and Ermentrout, G.B. (1989) Find in CUMINCAD Analysis of Neural Excitability and Oscillations, Methods in Neuronal Modeling , MIT Press, Cambridge, Massachusetts

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