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Saliency-based Image Retargeting in the Compressed Domain

机译:基于显着的图像retargeting在压缩域中

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In this paper, we propose a novel image retargeting algorithm to resize images based on the extracted saliency information from the compressed domain. Firstly, we utilize DCT coefficients in JPEG bitstream to perform saliency detection with the consideration of the human visual sensitivity. The obtained saliency information is used to determine the relative visual importance of each 8×8 block for the image. Furthermore, we propose a new adaptive block-level seam removal operation for connected blocks to resize the image. Thanks to the directly derived saliency information from the compressed domain, the proposed image retargeting algorithm effectively preserves the objects of attention, efficiently removes the less crucial regions, and therefore significantly outperforms the relevant state-of-the-art algorithms, as demonstrated with the careful analysis and in the extensive experiments.
机译:在本文中,我们提出了一种新颖的图像重试算法来基于来自压缩域的提取的显着信息来调整图像的大小。首先,我们利用JPEG比特流中的DCT系数,以考虑人类的视觉敏感性来执行显着性检测。所获得的显着信息用于确定图像的每个8×8块的相对视觉重要性。此外,我们提出了一种用于连接块的新的自适应块级接缝移除操作以调整图像大小。由于从压缩域中的直接导出的显着性信息,所提出的图像复按分算法有效地保留了注意的物体,有效地消除了不太关键的区域,因此显着优于相关的最新算法,如图所示仔细分析和在广泛的实验中。

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