A possible mechanism of stochastic resonance in the light of an extra-classical receptive field model of retinal ganglion cells
| Autor: | Kamales Bhaumik, Sandip Sarkar, Kuntal Ghosh |
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| Rok vydání: | 2009 |
| Předmět: |
Retinal Ganglion Cells
General Computer Science Stochastic resonance media_common.quotation_subject Models Neurological Blob detection Noise (electronics) Retinal ganglion medicine Animals Humans Contrast (vision) Computer vision Linear combination Mathematics media_common Stochastic Processes Quantitative Biology::Neurons and Cognition business.industry Visual cortex medicine.anatomical_structure Receptive field Artificial intelligence Visual Fields business Algorithm Biotechnology |
| Zdroj: | Biological Cybernetics. 100:351-359 |
| ISSN: | 1432-0770 0340-1200 |
| Popis: | Traditionally the intensity discontinuities in an image are detected as zero-crossings of the second derivative with the help of a Laplacian of Gaussian (LOG) operator that models the receptive field of retinal Ganglion cells. Such zero-crossings supposedly form a raw primal sketch edge map of the external world in the primary visual cortex of the brain. Based on a new operator which is a linear combination of the LOG and a Dirac-delta function that models the extra-classical receptive field of the ganglion cells, we find that zero-crossing points thus generated, store in presence of noise, apart from the edge information, the shading information of the image in the form of density variation of these points. We have also shown that an optimal image contrast produces best mapping of the shading information to such zero-crossing density variation for a given amount of noise contamination. Furthermore, we have observed that an optimal amount of noise contamination reproduces the minimum optimal contrast and hence gives rise to the best representation of the original image. We show that this phenomenon is similar in nature to that of stochastic resonance phenomenon observed in psychophysical experiments. |
| Databáze: | OpenAIRE |
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