Information Recovery From Rank-Order Encoded Images

Sen, Basabdatta B.

Abstract

The time to detection of a visual stimulus by the primate eye is recorded at 100-150ms. This near instantaneous recognition is in spite of a lot of processing by the several stages of the visual pathway to actually recognise and react to a visual scene. How this is achieved is still a matter of speculation. Rank-order code is a hypothesis proposed as a means of encoding adopted by the primate eye in rapid transmission of the initial burst of information from sensory neurons to the brain. We study efficiency of rank-order codes in encoding perceptually-important information in an image. VanRullen and Thorpe built a model of the ganglion cell layers of the retina to simulate and study the viability of rank-order as a means of encoding being followed by retinal neurons. We validate their model and quantify the information retrieved from rank-order encoded images in terms of the visually-important information recovered. Towards this goal, we apply the "perceptual information preservation algorithm", proposed by Petrovic and Xydeas after slight modification. We observe a low information recovery due to losses suffered during rank-order encoding and decoding processes. We propose to minimise these losses to recover maximum information in minimum time from rank-order encoded images. We first maximise information recovery by using pseudo-inverse of a filter-bank matrix to minimise losses during rank-order decoding. We then apply the biological principle of lateral inhibition to minimise losses during rank-order encoding. In doing so, we propose the Filter-overlap Correction algorithm. To test the performance of rank-order codes in a biologically realistic set-up, we design and simulate a model of the foveal-pit ganglion cells of the retina keeping close to biological parameters. We use this as a rank-order encoder and analyse its performance with respect to VanRullen and Thorpe's retinal model.

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