Multi-operator image retargeting based on automatic quality assessment

Image retargeting aims to avoid visual distortion while retaining important image content in resizing. However, no single image retargeting method can handle all cases. In this paper, we propose a novel multi-operator image retargeting approach, which utilizes an efficient and human perception based automatic quality assessment in operator selection. First, we calculate the importance map and distortion map for quality assessment. Then, we construct the resizing space and assess the performance of each operator in iterative width and/or height reduction. Finally, we select the optimal operator sequence by dynamic programming and generate the target image. Experiments demonstrate the effectiveness of the proposed approach.