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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ashutosh, D. Bose, N.S.C. Kandula, P. Kalra, P.K. |
| Copyright Year | 2007 |
| Description | Author affiliation: Indian Inst. of Technol., Kanpur (Ashutosh, D.; Bose, N.S.C.; Kandula, P.; Kalra, P.K.) |
| Abstract | Reduction of the image colors, which is also called color quantization (CQ), has been the focus of recent research interest. It is as an integral part of various digital image related areas such as compression, segmentation etc.. Neural networks play a significant role in either assisting conventional color quantization techniques or providing standalone solutions for color quantization. In the present work three new algorithms have been proposed using modified forward only counterpropogation network (MFOCPN). These algorithms introduce, 1) sub-clustering in Kohonen layer for enhancing the clustering process, 2) a new entropy metric based initialization of the Kohonen layer for efficient color-map design and faster convergence of network. Further, the two approaches are merged, to yield third algorithm to achieve better results. The proposed algorithms have been tested on standard test image. |
| Starting Page | 1865 |
| Ending Page | 1870 |
| File Size | 1810615 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424413799 |
| ISSN | 10987576 |
| DOI | 10.1109/IJCNN.2007.4371242 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-08-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Quantization Entropy Clustering algorithms Testing Focusing Digital images Image coding Image segmentation Neural networks Algorithm design and analysis |
| Content Type | Text |
| Resource Type | Article |
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