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    • 摘要: 光场成像能同时记录光线的强度信息与方向信息且具备估计场景深度的能力。然而,深度估计的精度却容易受光场遮挡的影响。因此,本文提出一种边框加权角相关的深度估计方法来解决该问题。首先,该方法将光场角度域图像分成四个边框子集并分别度量这些子集中像素的相关性来构建四个代价体积,以此解决不同类型的遮挡。其次,该方法提出加权融合策略来融合四个代价体积,进一步增强算法的鲁棒性,同时保留算法的抗遮挡能力。最后,融合后的代价体积利用引导滤波对其进行优化,以提升深度估计的精度。实验结果表明,提出的方法在量化指标上优于现有的方法。同时,在绝对深度测量实验中,提出的方法能实现高精度的测量。

       

      Abstract: Light field imaging recodes not only the intensity information of the rays, but also its direction information, and has the ability to estimate the depth of the scene. However, the accuracy of the depth estimation is easily influenced by light field occlusion. This paper proposes a method of weighted side window angular coherence to deal with different types of occlusions. Firstly, the angular patch is divided into four side window subsets, and the coherence of the pixels in these subsets is measured to construct four cost volumes to solve different types of occlusion. Secondly, the weighted fusion strategy is proposed to fuse the four cost volumes to further enhance the robustness of the algorithm and retain the anti-occlusion of the algorithm. Finally, the fused cost volume is optimized by the guided filter to further improve the accuracy of depth estimation. Experimental results show that the proposed method is superior to the existing methods in the quantitative index and can achieve high-precision measurement in the absolute depth measurement experiment.