Content-aware image retargeting is a technique that resizes images for optimum display on devices with different resolutions and aspect ratios. Traditional objective quality of experience (QoE) assessment methods are not applicable to retargeted images because the size of a retargeted image is different from its source. Dr. Jiangyang Zhang, a former MCL member and Professor C.-C. Jay Kuo, MCL Director, identified three main determining factors for humans visual QoE on retargeted images. They are global structural distortion (G), local region distortion (L) and loss of salient information (S). Zhang and Kuo selected features to quantify these respective distortion degrees and developed objective quality assessment index, called GLS, to predict viewers’ QoE by fusing selected features into one single quality score. The proposed GLS quality index has stronger correlation with human QoE than other existing objective metrics in retargeted image quality assessment with respect to two subjective image retargeting quality databases. The work was presented in the ACM Multimedia Conference on November 5 in Orlando, Florida.
A joint photo of Dr. Zhang and Prof. Kuo and a photo of Prof. Kuo together with ACM MM conference organizers and a Keynote Speaker, Prof. Rosalind Picard of MIT Media Lab (number 3 from the right), are shown.