ADAPTIVE LEARNING-METHOD IN SELF-ORGANIZING MAP FOR EDGE-PRESERVING VECTOR QUANTIZATION
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | KIM, YK | ko |
| dc.contributor.author | Ra, Jong Beom | ko |
| dc.date.accessioned | 2013-03-02T21:19:26Z | - |
| dc.date.available | 2013-03-02T21:19:26Z | - |
| dc.date.created | 2012-02-06 | - |
| dc.date.created | 2012-02-06 | - |
| dc.date.issued | 1995-01 | - |
| dc.identifier.citation | IEEE TRANSACTIONS ON NEURAL NETWORKS, v.6, no.1, pp.278 - 280 | - |
| dc.identifier.issn | 1045-9227 | - |
| dc.identifier.uri | http://hdl.handle.net/10203/75571 | - |
| dc.description.abstract | The Kohonen's Self-Organizing Map algorithm for vector quantization of images is modified to reduce the edge degradation in the coded image. The learning procedure is performed by adaptive learning rates that are determined according to the image block activity. The simulation result of 4x4 vector quantization for 512x512 image coding demonstrates the feasibility; of the proposed method. | - |
| dc.language | English | - |
| dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
| dc.title | ADAPTIVE LEARNING-METHOD IN SELF-ORGANIZING MAP FOR EDGE-PRESERVING VECTOR QUANTIZATION | - |
| dc.type | Article | - |
| dc.identifier.wosid | A1995QA72100031 | - |
| dc.identifier.scopusid | 2-s2.0-0029196895 | - |
| dc.type.rims | ART | - |
| dc.citation.volume | 6 | - |
| dc.citation.issue | 1 | - |
| dc.citation.beginningpage | 278 | - |
| dc.citation.endingpage | 280 | - |
| dc.citation.publicationname | IEEE TRANSACTIONS ON NEURAL NETWORKS | - |
| dc.contributor.localauthor | Ra, Jong Beom | - |
| dc.contributor.nonIdAuthor | KIM, YK | - |
| dc.type.journalArticle | Letter | - |
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