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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 9 , ISSUE 4 (December 2016) > List of articles


Qun Zhou * / Xiongwei Liu

Keywords : Image compression, quality assessment, objective assessment, blind assessment, image variance.

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 9, Issue 4, Pages 2,131-2,148, DOI: https://doi.org/10.21307/ijssis-2017-956

License : (CC BY-NC-ND 4.0)

Received Date : 29-July-2015 / Accepted: 18-January-2016 / Published Online: 01-December-2016



The assessment of image compression result can not only evaluate the quality of image
compression results and to a certain extent, can also find the advantages and drawbacks of various
compression methods. At the same time, it can provide a reference for the compressed image
restoration. Firstly, the classification and shortages of image quality assessment methods are presented.
Then, several objective assessment methods usually used for image compression quality are introduced
and the recent research progresses are shown. Finally, in view of the shortages of traditional image
assessment methods and the existing blind assessment methods, based on image invariance, we propose
a blind assessment method of image compression quality by considering the edge detail recovery and
artifact removing. Compared with the traditional blind assessment methods, our method is simple in
form and evaluation system is easily implemented. The experimental results also show that it is
reasonable and effective.

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