What is the goal of sensory coding?
Neural Computation
The visible differences predictor: an algorithm for the assessment of image fidelity
Digital images and human vision
CNS '97 Proceedings of the sixth annual conference on Computational neuroscience : trends in research, 1998: trends in research, 1998
Scientific Computing: An Introductory Survey
Scientific Computing: An Introductory Survey
Subjective tests for image fusion evaluation and objective metric validation
Information Fusion
A class of sparsely connected autoassociative morphological memories for large color images
IEEE Transactions on Neural Networks
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Which model to use for cortical spiking neurons?
IEEE Transactions on Neural Networks
Coding static natural images using spiking event times: do neurons Cooperate?
IEEE Transactions on Neural Networks
Sparse Distributed Memory Using Rank-Order Neural Codes
IEEE Transactions on Neural Networks
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In this paper, we present biologically inspired means to enhance perceptually important information retrieval from rank-order encoded images. Validating a retinal model proposed by VanRullen and Thorpe, we observe that on average only up to 70% of the available information can be retrieved from rank-order encoded images. We propose a biologically inspired treatment to reduce losses due to a high correlation of adjacent basis vectors and introduce a filter-overlap correction algorithm (FoCal) based on the lateral inhibition technique used by sensory neurons to deal with data redundancy. We observe a more than 10% increase in perceptually important information recovery. Subsequently, we present a model of the primate retinal ganglion cell layout corresponding to the foveal-pit. We observe that information recovery using the foveal-pit model is possible only if FoCal is used in tandem. Furthermore, information recovery is similar for both the foveal-pit model and VanRullen and Thorpe's retinal model when used with FoCal. This is in spite of the fact that the foveal-pit model has four ganglion cell layers as in biology while VanRullen and Thorpe's retinal model has a 16-layer structure.