Image Retargeting by Content-Aware Synthesis

Real-world images usually contain vivid contents and rich textural details, which will complicate the manipulation on them. In this paper, we present a content-aware synthesis method to enhance content-aware image retargeting. By detecting the textural regions in an image, the image content can be synthesized rather than simply distorted or cropped. This method enables the manipulation of textural & non-textural regions with different strategy since they have different natures. We propose to resize the textural regions by content-aware synthesis and non-textural regions by fast multioperators. To achieve practical resizing applications for general images, we develop an automatic and fast texture detection method that can detect multiple disjoint textural regions. We adjust the saliency of the image according to the features of the textural regions. To validate the proposed method, comparisons with state-ofthe-art resizing techniques and a user study were conducted. Convincing visual results are shown to demonstrate the effectiveness of the proposed method.