Author:
V. Antsiperov
Affiliation:
Kotelnikov Institute of Radioengineering and Electronics of RAS, Mokhovaya 11-7, Moscow, Russian Federation
Keyword(s):
Neuromorphic Systems, Poisson Counts, Sampling Representation, Receptive Fields, Lateral Inhibition, Poisson Disorder Problem, Colour Constancy, Retinex, Edge-Directed Interpolation, Perceptual Quality.
Abstract:
The paper discusses one of the possible neuromorphic methods for processing relatively large volumes of streaming data. The method is mainly motivated by the known mechanisms of sensory perception of living systems, in particular, methods of visual perception. In this regard, the main provisions of the method are discussed in the context of problems of encoding/recovering images on the periphery of the visual system. The proposed method is focused on representing input data in the form of a stream of discrete events (counts), like the firing events of retinal neurons. For these purposes, a special representation of data streams is used in the form of a controlled size samples of counts (sampling representations). Based on the specifics of the sampling representation, the generative data model is naturally formalized in the form of a system of components distributed over the field of view. These components are equipped with some “neuromorphic” structure, which model a system of recept
ive fields, embodying universal principles (including lateral inhibition) of the neural network of the brain. The mechanism of lateral inhibition is implemented in the model in the form of an antagonistic structure of the RF centre / surround. Issues of image decoding are considered in the context of restoring spatial contrasts, which partly emulates the work of the so-called simple / complex cells of the primary visual cortex. It is shown that the model of coupled ON-OFF decoding allows for the restoration of sharp image details in the form of emphasizing edges.
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