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Color image compression using self organizing feature map

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dc.contributor.authorDiri, B
dc.contributor.authorAlbayrak, S
dc.contributor.institutionauthorVARLI, Songül
dc.date.accessioned2026-06-27T13:00:11Z
dc.date.issued2006
dc.description.abstractThis paper presents a compression scheme for color images, by using Self-Organizing Feature Map (SOFM) algorithm, which is a neural network structure. In this application 1-dimensional SOFM is used to map 256-color to 64-, 32- and 16-color. After the quantization process, relative coding and entropy coding are performed without any loss in the information. Obtained results encourage the use of SOFM for image compression.en
dc.identifier.endpage+
dc.identifier.isbn0-88986-556-6
dc.identifier.startpage162
dc.identifier.urihttps://hdl.handle.net/20.500.14981/48828
dc.identifier.wos000236387300028
dc.language.isoeng
dc.publisherACTA PRESS
dc.relation.conferenceIASTED International Conference on Artificial Intelligence and Applications
dc.relation.ispartofPROCEEDINGS OF THE IASTED INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND APPLICATIONS
dc.subjectimage compression
dc.subjectcolor quantization
dc.subjectI-D self-organizing feature map
dc.subjectentropy coding
dc.subjectComputer Science
dc.titleColor image compression using self organizing feature map
dc.typeProceedings Paper
dspace.entity.typePublication
local.import.sourceWOS

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