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Evaluation of the Medical Image Compression using Wavelet Packet Transform and SPIHT Coding

International Journal of Electrical and Computer Engineering (IJECE) · Vol. 8 No. 4 (2018)

DOI
10.11591/ijece.v8i4.pp2139-2147
ISSN
2088-8708, 2088-8708
Published
2018-08-01
Publisher
Institute of Advanced Engineering and Science
License
creativecommons.org/licenses/by-nc/4.0

Abstract

Wavelet transforms and wavelet packets are widely imposed in the analysis and resolution of problems related to science and technical engineering. Decomposition wavelet packet allows several frequency bands according to various levels of resolutions. We apply this transform (PWT) coupled with the SPIHT coder to reduce the limitations of conventional wavelet filter bank. The results obtained using the applied algorithm, are very satisfactory and encouraging compared to many of the best coders cited in the literature and show a visual and numerical superiority over conventional methods. These the promising results are confirmed by visual evaluation parameters (PSNR, MSSIM and VIF).

Collaboration network of the authors

7 authors · 9 co-authorship links · 3 across different organisations

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  • University of Bechar
  • Centre universitaire Salhi Ahmed - Naama
  • Badji Mokhtar-Annaba University
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
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Co-authorOrganisationJoint articles
Yassine HabchiUniversity of Bechar2
Abdelmalik Taleb AhmedUniversity of Bechar2
Rekkal KahinaCentre universitaire Salhi Ahmed - Naama2
Rekkal SaraBadji Mokhtar-Annaba University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

This record comes from Crossref (what the publisher deposited), because the journal's own OAI-PMH endpoint could not be harvested.

Metadata source: Crossref API (cadangan, berdasarkan ISSN) https://api.crossref.org/journals/2088-8708/works, first harvested 27 Okt 2026, last seen 27 Okt 2026.
Metadata as oai_dc, converted from Crossref
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