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Exploiting the Value of the Center-dark Channel Prior for Salient Object Detection

机译:在突出对象检测之前利用中心黑通道的值

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摘要

Saliency detection aims to detect the most attractive objects in images and is widely used as a foundation for various applications. In this article, we propose a novel salient object detection algorithm for RGB-D images using center-dark channel priors. First, we generate an initial saliency map based on a color saliency map and a depth saliency map of a given RGB-D image. Then, we generate a center-dark channel map based on center saliency and dark channel priors. Finally, we fuse the initial saliency map with the center dark channel map to generate the final saliency map. Extensive evaluations over four benchmark datasets demonstrate that our proposed method performs favorably against most of the state-of-the-art approaches. Besides, we further discuss the application of the proposed algorithm in small target detection and demonstrate the universal value of center-dark channel priors in the field of object detection.
机译:显着性检测旨在检测图像中最具吸引力的物体,并且被广泛用作各种应用的基础。在本文中,我们使用中心暗通道前沿提出了一种用于RGB-D图像的新型突出物体检测算法。首先,我们基于色调图和给定RGB-D图像的深度显着图生成初始显着图。然后,我们基于中心显着性和暗通道前沿生成中心暗信道地图。最后,我们将初始显着性图融合了中心黑暗信道地图,以生成最终显着图。四个基准数据集的广泛评估表明,我们的建议方法对大多数最先进的方法进行了有利的方法。此外,我们进一步讨论了在小目标检测中的提出算法的应用,并证明了物体检测领域中的中心暗通道前沿的普遍值。

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