Various methods have been performed for the purpose of Low Dynamic Range (LDR) image retrieval. However, no major work concerning the High Dynamic Range (HDR) image indexing has been widely diffused yet. We therefore propose a method that tackles the problem of efficiently and accurately retrieving HDR images. The proposed system is based on a hybrid descriptor which combines two color features. The first one is histogram based on the hue–saturation–value (HSV) color space that approaches the perception of human vision, whereas the second comprises the first- and second-order moments of the color bands. As a dissimilarity measure, we retained the Manhattan distance. In the second part of our work, we proposed an automatic tone mapping operator (TMO) to get an overview on the result images by using Standard Dynamic Range (SDR) devices. Comparisons with recent state-of-the-art TMOs have shown that our TM method produces LDR images with adequate quality while maintaining low complexity. Finally, to test our retrieval system, we have created two databases. Experimental evaluation showed that our system supports HDR images while achieving satisfying results in terms of accuracy and computational cost.

中文翻译：

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使用基于颜色的描述符和色调映射算子的 HDR 图像检索

为了低动态范围 (LDR) 图像检索的目的，已经执行了各种方法。然而，关于高动态范围 (HDR) 图像索引的主要工作尚未广泛传播。因此，我们提出了一种方法来解决高效准确地检索 HDR 图像的问题。所提出的系统基于结合了两种颜色特征的混合描述符。第一个是基于接近人类视觉感知的色调饱和度值 (HSV) 颜色空间的直方图，而第二个包含色带的一阶和二阶矩。作为差异性度量，我们保留了曼哈顿距离。在我们工作的第二部分，我们提出了一种自动色调映射算子 (TMO)，通过使用标准动态范围 (SDR) 设备来概览结果图像。与最近最先进的 TMO 的比较表明，我们的 TM 方法生成的 LDR 图像具有足够的质量，同时保持低复杂性。最后，为了测试我们的检索系统，我们创建了两个数据库。实验评估表明，我们的系统支持 HDR 图像，同时在准确性和计算成本方面取得了令人满意的结果。