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Using perceptually weighted histograms for colour-based image retrieval

机译:对基于颜色的图像检索的感知加权直方图

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In common colour-based image retrieval, colour histograms for images in the database and queries are calculated. The distance between a query and each of the database images is calculated as the sum of the absolute values of bin-to-bin differences between their histograms. The method ignores colour similarity between bins, leading to cases where perceptually similar images have very large histogram distances. In this paper, we propose to use perceptually weighted histograms (PWH) to overcome the problem. In PWH, a pixel contributes weights to a number of perceptually similar bins instead of a single bin. The contributing weights are inversely proportional to the distance between the pixel and bins.
机译:在普通的基于颜色的图像检索中,计算数据库中的图像的颜色直方图和查询。查询和每个数据库图像之间的距离被计算为它们直方图之间的箱到箱差的绝对值之和。该方法忽略箱之间的颜色相似性,导致感知相似的图像具有非常大的直方图距离的情况。在本文中,我们建议使用感知加权直方图(PWH)来克服问题。在PWH中,像素将权重到多个感知相似的箱而不是单个箱。贡献权重与像素和箱之间的距离成反比。

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