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Contour Sensitive Saliency and Depth Application in Image Retargeting

机译：轮廓敏感显着性和深度在图像重定向中的应用

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摘要

Image retargeting technique requires important information preservation and less edge distortion during increasing/decreasing image size. The major existed content-aware methods perform well. However, there are two problems should be improved: the slight distortion appeared at the object edges and the structure distortion in the non-salient area. According to psychological theories, people evaluate image quality based on multi-level judgments and comparison between different areas, both image content and image structure. The paper proposes a new standard: the structure preserving in non-salient area. After observation and image analysis, blur (slight blur) is generally existed at the edge of objects. The blur feature is used to estimate the depth cue, named blur depth descriptor. It can be used in the process of saliency computation for balanced image retargeting result. In order to keep the structure information in non-salient area, the salient edge map is presented in Seam Carving process, instead of field-based saliency computation. The derivative saliency from x- and y-direction can avoid the redundant energy seam around salient objects causing structure distortion. After the comparison experiments between classical approaches and ours, the feasibility of our algorithm is proved.
机译：图像重定目标技术要求重要的信息保留以及在增加/减小图像尺寸时减少边缘变形。现有的主要的内容感知方法表现良好。但是，有两个问题需要改进：在对象边缘出现轻微的变形，在非突出区域出现结构变形。根据心理学理论，人们根据多层次的判断以及图像内容和图像结构之间不同区域之间的比较来评估图像质量。本文提出了一个新的标准：在非盐碱地带保存结构。经过观察和图像分析后，物体边缘通常存在模糊（轻微模糊）。模糊功能用于估计深度提示，称为模糊深度描述符。它可以在显着性计算过程中用于平衡图像重定目标结果。为了将结构信息保持在非突出区域，在接缝雕刻过程中提供了显着边缘图，而不是基于字段的显着性计算。 x和y方向的导数显着性可以避免在凸出物体周围形成多余的能量线，从而导致结构变形。通过与经典方法的对比实验，证明了该算法的可行性。

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