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A multiscale image compressor with RBFNN and Discrete Wavelet decomposition

  • University of Catania
  • Częstochowa University of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

43 Citations (Scopus)

Abstract

This work presents a new adaptive technique for image compression based on Discrete Wavelet Transform (DWT) and Radial Basis Function Neural Networks (RBFNN). The technique can be employed both for lossless and lossy (higher) compression and has been devised in order to deal effectively with a large variety of images. Proposed solution performs well both in terms of computing time and memory. Its generality, flexibility and efficiency make it attractive for storage and transmission in the field of vision and multimedia systems.

Original languageEnglish
Title of host publication2015 International Joint Conference on Neural Networks, IJCNN 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479919604, 9781479919604, 9781479919604, 9781479919604
DOIs
Publication statusPublished - 28 Sept 2015
EventInternational Joint Conference on Neural Networks, IJCNN 2015 - Killarney, Ireland
Duration: 12 Jul 201517 Jul 2015

Publication series

NameProceedings of the International Joint Conference on Neural Networks
Volume2015-September

Conference

ConferenceInternational Joint Conference on Neural Networks, IJCNN 2015
Country/TerritoryIreland
CityKillarney
Period12/07/1517/07/15

Keywords

  • Decoding
  • Discrete wavelet transforms
  • Image coding
  • Nickel
  • Optical imaging

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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