DCT-based objective quality assessment metric of 2D/3D image

With the increasing growth of multimedia applications over the networking in recent years, users have put forward much higher requirements for multimedia quality of experience (QoE) than before. One of the representative requirements is the image quality. Therefore, the image quality assessment ranging from two-dimension (2D) image to three-dimension (3D) image has been getting much attention. In this paper, an efficient objective image quality assessment metric in block-based discrete cosine transform (DCT) coding is proposed. The metric incorporates properties of human visual system (HVS) to improve its validity and reliability in evaluating the quality of stereoscopic image. This is fulfilled by calculating the local pixel-based distortions in frequency domain, combining the simplified models of local visibility properties embodied in frequency domain, which consist of region of interest (ROI) mechanism (visual sensitivity), contrast sensitivity function (CSF) and contrast masking effect. The performance of the proposed metric is compared with other currently state-of-the-art objective image quality assessment metrics. The experimental results have demonstrated that the proposed metric is highly consistent with the subjective test scores. Moreover, the performance of the metric is also confirmed with the popular IRCCyN/IVC database. Therefore, the proposed metric is promising in term of the practical efficiency and reliability for real-life multimedia applications.