Automatic image retargeting evaluation based on user perception

Tongwei Ren, Gangshan Wu

Abstract: As image retargeting techniques have attracted more and more attention for effective image display on mobile devices, quality evaluation of image retargeting is required. To address the lack of automatic evaluation techniques in retargeting, this paper proposes a user perception based framework to automatically evaluate the quality of the target image against the original image. In the framework, the pixels in the original image and the target image are first approximately order-preserved matched by dynamic programming. Based on the pixel matching result, several features are extracted to describe the user requirements and further adapted to fit user perception in retargeting. Finally, the overall score of the target image quality is calculated by integrating the scores in different evaluation aspects. Experiments demonstrate the effectiveness of the proposed framework.