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.
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