Title :
Reduced-reference image quality assessment in modified reorganized DCT domain
Author :
Zhi Wang;Kai Xu;Shi Yan
Author_Institution :
School of Information Science and Engineering, Lanzhou University, Lanzhou 730000, P. R. China
Abstract :
The objective of reduced-reference (RR) image quality assessment (IQA) is to evaluate the perceptual quality of the distorted image with only partial information of the reference image. A novel RR IQA which calculates the information entropy in the modified reorganized discrete cosine transform (RDCT) domain is introduced in this paper. Firstly, on the sender side, the modified RDCT is applied to decompose the reference image into 10 sub-bands, which accords with the channel decomposition property of human visual system (HVS). Subsequently, the information entropy of selective sub-bands is extracted as features of reference image. Finally, on the receiver side, the same procedure is employed to the distorted image, and the difference of features between reference and distorted image is fused to generate the quality measure of distorted image. The experimental results demonstrates that our proposed RR IQA can outperform the state-of-the-art RR IQAs and even the full-reference IQA.
Keywords :
"Discrete cosine transforms","Feature extraction","Distortion","Image quality","Information entropy","Distortion measurement","Data mining"
Conference_Titel :
Computer and Communications (ICCC), 2015 IEEE International Conference on
Print_ISBN :
978-1-4673-8125-3
DOI :
10.1109/CompComm.2015.7387560