Bare bones fireworks algorithm for medical image compression

Eva Tuba, Raka Jovanovic, Marko Beko, Antonio J. Tallón-Ballesteros, Milan Tuba

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

4 Citations (Scopus)


Digital images are of a great importance in medicine. Efficient and compact storing of the medical digital images represents a major issue that needs to be solved. JPEG lossy compression algorithm is most widely used where better compression to quality ratio can be obtained by selecting appropriate quantization tables. Finding the optimal quantization tables is a hard combinatorial optimization problem and stochastic metaheuristics have been proven to be very efficient for solving such problems. In this paper we propose adjusted bare bones fireworks algorithm for quantization table selection. The proposed method was tested on different medical digital images. The results were compared to the standard JPEG algorithm. Various image similarity metrics were used and it has been shown that the proposed method was more successful.

Original languageEnglish
Title of host publicationIntelligent Data Engineering and Automated Learning – IDEAL 2018 - 19th International Conference, Proceedings
EditorsDavid Camacho, Paulo Novais, Antonio J. Tallón-Ballesteros, Hujun Yin
PublisherSpringer Verlag
Number of pages9
ISBN (Print)9783030034955
Publication statusPublished - 1 Jan 2018
Event19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018 - University Autónoma de Madrid, Madrid, Spain
Duration: 21 Nov 201823 Nov 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11315 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018
Abbreviated title IDEAL 2018


  • Bare bones fireworks algorithm
  • Compression
  • JPEG
  • Medical image processing
  • Optimization
  • Quantization tables


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