Image retargeting changes the aspect ratio of images while aiming to preserve content and minimise noticeable distortion. Fast and high-quality methods are particularly relevant at present, due to the large variety of image and display aspect ratios. We propose a retargeting method that quantifies and limits warping distortions with the use of content-aware cropping. The pipeline of the proposed approach consists of the following steps. First, an importance map of a source image is generated using deep semantic segmentation and saliency detection models. Then, a preliminary warping mesh is computed using axis aligned deformations, enhanced with the use of a distortion measure to ensure low warping deformations. Finally, the retargeted image is produced using a content-aware cropping algorithm. In order to evaluate our method, we perform a user study based on the RetargetMe benchmark. Experimental analyses show that our method outperforms recent approaches, while running in a fraction of their execution time.

本论文提出了一种基于内容感知裁剪的图像重塑方法，该方法通过生成源图像的重要性映射并使用语义分割和显著性检测模型计算初步扭曲网格，然后结合扭曲度量以确保最小变形，并使用内容感知裁剪算法生成新的目标图像，通过 RetargetMe 基准测试的用户研究分析表明我们的方法在执行时间的一小部分内胜过了其他现有的方法。

快速混合图像调整