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Objective quality assessment for image retargeting based on perceptual distortion and information loss

机译:基于感知扭曲和信息损失的图像retarging的客观质量评估

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Image retargeting techniques aim to obtain retargeted images with different sizes or aspect ratios for various display screens. Various content-aware image retargeting algorithms have been proposed recently. However, there is still no accurate objective metric for visual quality assessment of retargeted images. In this paper, we propose a novel objective metric for assessing visual quality of retargeted images based on perceptual geometric distortion and information loss. The proposed metric measures the geometric distortion of retargeted images by SIFT flow variation. Furthermore, a visual saliency map is derived to characterize human perception of the geometric distortion. On the other hand, the information loss in a retargeted image, which is calculated based on the saliency map, is integrated into the proposed metric. A user study is conducted to evaluate the performance of the proposed metric. Experimental results show the consistency between the objective assessments from the proposed metric and subjective assessments.
机译:图像retargeting技术旨在获得具有不同大小或宽高比的标准图像,用于各种显示屏。最近已经提出了各种内容感知图像retararting算法。但是,仍然没有准确的客观度量,可视化质量评估重返图像。在本文中,我们提出了一种基于感知几何失真和信息丢失的基于感知几何失真和信息损失来评估重次图像的视觉质量的新颖的客观度量。所提出的度量通过SIFT流动变化测量returared图像的几何失真。此外,导出视力效率图以表征对几何失真的人类感知。另一方面,基于显着图计算的retargeted图像中的信息丢失集成到所提出的指标中。进行用户学习以评估所提出的指标的性能。实验结果表明,拟议的指标和主观评估的客观评估之间的一致性。

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