Huang, C.-H. ; Koeppl, H. (2007)
A Bio-inspired Computer Fovea Model based on hexagonal-type cellular neural networks.
In: IEEE Transactions on circuits and systems-I : regular papers, 54 (1)
Article, Bibliographie
Abstract
For decades, numerous scientists have examined the following questions: “How do humans see the world?” and “How do humans experience vision?” To answer these questions, this study proposes a computer fovea model based on hexagonal-type cellular neural network (hCNN). Certain biological mechanisms of a retina can be simulated using an in-state-of-art architecture named CNN. Those biological mechanisms include the behaviors of the photoreceptors, horizontal cells, ganglions, and bipolar cells, and their co-operations in the retina. Through investigating the model and the abilities of the CNN, various properties of the human vision system can be simulated. The human visual system possesses numerous interesting properties, which provide natural methods of enhancing visual information. Various visual information enhancing algorithms can be developed using these properties and the proposed model. The proposed algorithms include color constancy, image sharpness, and some others. This study also discusses how the proposed model works for video enhancement and demonstrates it experimentally.
| Item Type: | Article |
|---|---|
| Erschienen: | 2007 |
| Creators: | Huang, C.-H. ; Koeppl, H. |
| Type of entry: | Bibliographie |
| Title: | A Bio-inspired Computer Fovea Model based on hexagonal-type cellular neural networks |
| Language: | English |
| Date: | 2007 |
| Place of Publication: | Vancouver, BC |
| Publisher: | IEEE |
| Journal or Publication Title: | IEEE Transactions on circuits and systems-I : regular papers |
| Volume of the journal: | 54 |
| Issue Number: | 1 |
| Event Title: | IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS�I: REGULAR PAPERS, VOL. 54, NO. 1, JANUARY 2007 |
| URL / URN: | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4061016 |
| Abstract: | For decades, numerous scientists have examined the following questions: “How do humans see the world?” and “How do humans experience vision?” To answer these questions, this study proposes a computer fovea model based on hexagonal-type cellular neural network (hCNN). Certain biological mechanisms of a retina can be simulated using an in-state-of-art architecture named CNN. Those biological mechanisms include the behaviors of the photoreceptors, horizontal cells, ganglions, and bipolar cells, and their co-operations in the retina. Through investigating the model and the abilities of the CNN, various properties of the human vision system can be simulated. The human visual system possesses numerous interesting properties, which provide natural methods of enhancing visual information. Various visual information enhancing algorithms can be developed using these properties and the proposed model. The proposed algorithms include color constancy, image sharpness, and some others. This study also discusses how the proposed model works for video enhancement and demonstrates it experimentally. |
| Divisions: | 18 Department of Electrical Engineering and Information Technology 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications > Bioinspired Communication Systems 18 Department of Electrical Engineering and Information Technology > Institute for Telecommunications |
| Date Deposited: | 04 Apr 2014 14:23 |
| Last Modified: | 23 Sep 2021 14:32 |
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