Reduced-reference quality assessment for retargeted images

Recent years have witnessed tremendous growth in the generation and consumption of digital images. Monitoring and evaluating image quality is an important issue for online and mobile media applications. Conventional quality assessment work mostly focus on intensity level distortion caused by operations that do not change image size. In this work, we study the problem of quality assessment for images having undergone content-adaptive resizing, also known as retargeting operations. We design a reduced-reference algorithm to analyze the structural distortion caused by retargeting and propose a quality score that achieves positive correlation with human observations. The quality score and distortion analysis from the proposed algorithm provide rich information for both objective and subjective quality assessment tasks.