Biologically inspired means for rank-order encoding images: a quantitative analysis.
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.
Sen Bhattacharya
Basabdatta
B
Intelligent Systems Research Center, University of Ulster, Derry BT48 7JL, UK. basab815@gmail.com
Furber
Stephen B
SB
D000465:Algorithms; D000818:Animals; D003952:Diagnostic Imaging / Q000379:methods*; D005584:Fovea Centralis / Q000166:cytology; D007091:Image Processing, Computer-Assisted; D016247:Information Storage and Retrieval; D008959:Models, Neurological; D009433:Neural Inhibition / Q000502:physiology; D016571:Neural Networks, Computer; D011323:Primates; D015203:Reproducibility of Results; D012160:Retina / Q000166:cytology; D012165:Retinal Ganglion Cells / Q000502:physiology*; D014795:Visual Pathways / Q000502:physiology