Abstract
This paper is concerned with the degradation produced in natural images by JPEG compression. Our study has been basically twofold: (i) To find relationships between the amount of compression-induced degradation in an image and its various statistical properties. The goal is to identify blocks that will exhibit lower/higher rates of degradation as the degree of compression increases. (ii) To compare the above objective characterizations with subjective assessments of observers.
The conclusions of our study are rather significant in several aspects. First of all, “bad” blocks, i.e., blocks exhibiting greater degrees of degradation visually, have among the lowest RMSEs of all blocks and among the medium-to-highest structural similarity (SSIM)-based errors. Secondly, the standard deviations of “bad” blocks are among the lowest of all blocks, suggesting a kind of “Weber law for compression,” a consequence of contrast masking. Thirdly, “bad” blocks have medium-to-high high-frequency (HF) fractions as opposed to HF content.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Brunet, D., Vrscay, E.R., Wang, Z.: On the mathematical properties of the structural similarity index. IEEE Trans. Image Process. 21(4), 1488–1499 (2012)
Wang, Z., Bovik, A.C.: Mean squared error: love it or leave it? a new look at signal fidelity measures. IEEE Sig. Process. Mag. 26(1), 98–117 (2009)
Wang, Z., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(1), 600–612 (2004)
Kowalik-Urbaniak, I.A., et al.: The quest for “diagnostically lossless” medical image compression: a comparative study of objective quality metrics for compressedmedical images. In: SPIE Medical Imaging 2014. doi:10.1117/12:2043196
Rao, K.R., Hwang, J.J.: Techniques and Standards for Image, Video and Audio Coding. Prentice Hall, New York (1996)
Acknowledgements
This research was supported in part by a Discovery Grant (ERV) from the Natural Sciences and Engineering Research Council of Canada.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Cheeseman, A.K., Kowalik-Urbaniak, I.A., Vrscay, E.R. (2016). Objective Image Quality Measures of Degradation in Compressed Natural Images and their Comparison with Subjective Assessments. In: Campilho, A., Karray, F. (eds) Image Analysis and Recognition. ICIAR 2016. Lecture Notes in Computer Science(), vol 9730. Springer, Cham. https://doi.org/10.1007/978-3-319-41501-7_19
Download citation
DOI: https://doi.org/10.1007/978-3-319-41501-7_19
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-41500-0
Online ISBN: 978-3-319-41501-7
eBook Packages: Computer ScienceComputer Science (R0)