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Near Lossless JPEG Compression Based on Masking Effect of Non-predictable Energy of Image Regions

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


Original languageEnglish
Title of host publicationImage Analysis - 21st Scandinavian Conference, SCIA 2019, Proceedings
EditorsMichael Felsberg, Per-Erik Forssén, Jonas Unger, Ida-Maria Sintorn
PublisherSpringer Verlag
Number of pages11
ISBN (Print)9783030202040
Publication statusPublished - 2019
Publication typeA4 Article in a conference publication
EventScandinavian Conference on Image Analysis - Norrköping, Sweden
Duration: 11 Jun 201913 Jun 2019

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


ConferenceScandinavian Conference on Image Analysis


This paper studies near lossless JPEG image compression. A method of estimation of image regions masking ability (maximal level of distortions invisible for human visual system) using non-predictable energy of image regions is described. A novel method of zeroing quantized DCT coefficients of JPEG images to increase their compression ratio without introducing visible distortions is proposed. A numerical analysis of effectiveness of the proposed near lossless compression method using 300 noise free test images of TAMPERE17 database is carried out. It is shown that the proposed method provides an increase of compression ratio of JPEG images without visible distortions at about 1.35 times in average. Additionally, the proposed method results in decreasing of variability of compression ratio values for different images. It is shown that the proposed method increases minimal compression ratio for highly textured JPEG images from 1.1…1.5 times to 2 times. Carried out experiments demonstrated once again that the traditional PSNR metric does not correspond to human perception for this task.


  • Human visual system, JPEG, Lossy image compression, Masking effect, Near lossless image compression

Publication forum classification

Field of science, Statistics Finland