A fast method of visually lossless compression of dental images

Sergey Krivenko, Vladimir Lukin, Olha Krylova, Liudmyla Kryvenko, Karen Egiazarian

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)

Abstract

A noniterative approach to the problem of visually lossless compression of dental images is proposed for an image coder based on the discrete cosine transform (DCT) and partition scheme opti-mization. This approach considers the following peculiarities of the problem. It is necessary to carry out lossy compression of dental images to achieve large compression ratios (CRs). Since dental images are viewed and analyzed by specialists, it is important to preserve useful diagnostic information preventing appearance of any visible artifacts due to lossy compression. At last, dental images may contain noise having complex statistical and spectral properties. In this paper, we have analyzed and utilized dependences of three quality metrics (Peak signal-to-noise ratio, PSNR; eak Signal-to-Noise Ratio using Human Visual System and Masking (PSNR-HVS-M); and feature similarity, FSIM) on the quantization step (QS), which controls a compression ratio for the so-called advanced DCT coder (ADCTC). The threshold values of distortion visibility for these metrics have been considered. Finally, the recent results on detectable changes in noise intensity have been incorporated in the QS setting. A visual comparison of original and compressed images allows to conclude that the introduced distortions are practically undetectable for the proposed approach; meanwhile, the provided CR lies within the interval.

Original languageEnglish
Article number135
Number of pages14
JournalApplied Sciences (Switzerland)
Volume11
Issue number1
Early online date25 Dec 2020
DOIs
Publication statusPublished - 2021
Publication typeA1 Journal article-refereed

Keywords

  • Dental image
  • Fast processing
  • Visually lossless compression

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Materials Science(all)
  • Instrumentation
  • Engineering(all)
  • Process Chemistry and Technology
  • Computer Science Applications
  • Fluid Flow and Transfer Processes

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