Near-lossless Image Compression with Parity Reduction

Basar Koc, Ziya Arnavut, Sergey Voronin, Huseyin Kocak

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In our previous work, we introduced a lossless image compression algorithm (called BWIC_I) based on hierarchical prediction, inversion, and context-adaptive coding techniques. We showed that BWIC_I outperformed most commonly used standard color image compression algorithms, including JPEG in lossless mode and JPEG 2000, on a variety of well-known image data sets. In this study, we introduce a near-lossless image compression algorithm that essentially consists of parity reduction by dropping the least significant bit of pixel values of RGB color images and then compressing the resulting data with BWIC_I. The proposed algorithm provides a guaranteed minimum PSNR value. Moreover, it does not require a specialized encoding and decoding algorithm and can be utilized in conjunction with other generic image compression algorithms. The compression performance of the proposed technique is considerably better than JPEG and JPEG 2000, as demonstrated on the standard Kodak image set.

Original languageEnglish (US)
Title of host publicationINES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages225-229
Number of pages5
ISBN (Electronic)9781728110592
DOIs
StatePublished - Jul 2020
Event24th IEEE International Conference on Intelligent Engineering Systems, INES 2020 - Reykjavik, Iceland
Duration: Jul 8 2020Jul 10 2020

Publication series

NameINES 2020 - IEEE 24th International Conference on Intelligent Engineering Systems, Proceedings

Conference

Conference24th IEEE International Conference on Intelligent Engineering Systems, INES 2020
CountryIceland
CityReykjavik
Period7/8/207/10/20

Keywords

  • BWIC_I
  • JPEG
  • JPEG 2000
  • Least significant bit
  • Near-lossless image compression
  • PSNR
  • Parity reduction
  • SSIM

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Decision Sciences (miscellaneous)
  • Control and Optimization

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