Kurtosis-based no-reference quality assessment of JPEG2000 images

Authors:
Jing Zhang;S. H. Ong;Thinh M. Le
Affiliations:
Department of Electrical and Computer Engineering, National University of Singapore, Block E4-05-45, 4 Engineering Drive 3, Singapore 117576, Singapore;Department of Electrical and Computer Engineering, National University of Singapore, Block E4-05-45, 4 Engineering Drive 3, Singapore 117576, Singapore and Division of Bioengineering, National Uni ...;Department of Electrical and Computer Engineering, National University of Singapore, Block E4-05-45, 4 Engineering Drive 3, Singapore 117576, Singapore
Venue:
Image Communication
Year:
2011

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Abstract

No-reference (NR) image quality assessment (QA) presumes no prior knowledge of reference (distortion-free) images and seeks to quantitatively predict visual quality solely from the distorted images. We develop kurtosis-based NR quality measures for JPEG2000 compressed images in this paper. The proposed measures are based on either 1-D or 2-D kurtosis in the discrete cosine transform (DCT) domain of general image blocks. Comprehensive testing demonstrates their good consistency with subjective quality scores as well as satisfactory performance in comparison with both the representative full-reference (FR) and state-of-the-art NR image quality measures.