Objective Performance of Compressed Image Quality Assessments
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Objective Performance of Compressed Image Quality Assessments

Authors: Ratchakit Sakuldee, Somkait Udomhunsakul


Measurement of the quality of image compression is important for image processing application. In this paper, we propose an objective image quality assessment to measure the quality of gray scale compressed image, which is correlation well with subjective quality measurement (MOS) and least time taken. The new objective image quality measurement is developed from a few fundamental of objective measurements to evaluate the compressed image quality based on JPEG and JPEG2000. The reliability between each fundamental objective measurement and subjective measurement (MOS) is found. From the experimental results, we found that the Maximum Difference measurement (MD) and a new proposed measurement, Structural Content Laplacian Mean Square Error (SCLMSE), are the suitable measurements that can be used to evaluate the quality of JPEG200 and JPEG compressed image, respectively. In addition, MD and SCLMSE measurements are scaled to make them equivalent to MOS, given the rate of compressed image quality from 1 to 5 (unacceptable to excellent quality).

Keywords: JPEG, JPEG2000, objective image quality measurement, subjective image quality measurement, correlation coefficients.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1074731

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[1] "Method for the Subjective Assessment of the Quality of Television Pictures," 1982, CCIR Rec. 500-2.
[2] ITU, "Methods for the Subjective Assessment of the Quality of Television Pictures," August 1998, ITU-R Rec. BT. 500-7.
[3] M. Eskicioglu and P. S. Fisher, "Image Quality Measures and Their Performance," IEEE Transactions on Communications, vol. 43, no. 12, December 1995, pp. 2959-2965.
[4] S. Grgic, M. Grgic and M. Mrak, "Reliability of Objective Picture Quality Measurement," Journal of Electrical Engineering, vol. 55, no. 1- 2, 2004, pp. 3-10.
[5] H. R. Sheikh, M. F. Sabir and A. C. Bovik, "A Statistical Evalution of Recent Full Recent Full Reference Image Quality Assessment Algorithms," IEEE Transactions on image processing, vol. 15, no. 11, November 2006, pp. 3441-3456.
[6] M. Miyahara, K. Kotani and V. R. Algazi, "Objective Picture Quality Scale (PQS) for Image Coding," IEEE Transactions on Communication, vol. 46, no. 9, September 1998.
[7] Z. Wang, H.R. Sheikh and A. C. Bovik, "Image Quality Assessment: From Error Visibility to Structural Similarity," IEEE Transactions of Image Processing, vol. 13, April 2004, pp. 1-12.
[8] Z. Wang and A.C. Bovik, "A Universal Image Quality Index, " IEEE Signal Processing Letters, vol. 9, No. 3, March 2002, pp. 81-84.
[9] H. M. Al-Otum, "Qualitative and quantitative image quality assessment of vector quantization, JPEG, and JPEG2000 compressed images," Journal of Electronic Imaging, vol. 12(3), July 2003, pp. 511-521.
[10] N. Yamsang and S. Udomhunsakul, "Distribution Model between Objective Measurement and Subjective Measurement," IEEE International Conference on Computer Science (RIVF), March 2007, pp. 81-86.