基于多方向滤波的强边缘深度图像补全方法

传统的深度相机能够获取像素级配准的深度和彩色图像，但所获取的深度图像存在明显的像素缺失。针对这一问题，文章提出了一种快速深度图像补全算法，能够有效地填充像素缺失区域并保持锐利的深度图像边缘特征。首先，设计出一种边缘蒙版，通过边缘蒙版对联合双边滤波器进行改进。其次，与传统滤波器算法不同，由于滤波器本身存在的方向特性，文章采用不同方向模拟了真实场景的遮挡情况。通过设定4个滤波方向，用改进后的联合双边滤波器对孔洞深度图进行修补填充，然后再通过马尔科夫随机场模型，将4个不同方向滤波器获得的深度填充图融合成一幅图像。最后，通过不同场景的深度图像进行实验。结果表明，所提出的深度图像补全算法显著优于传统方法。

Strong Edge-Aware Depth Image Completion with Multi-Direction Filtering

Conventional depth-camera can provide pixel-wise aligned depth and color images. However, the obtained depth image usually contains a lot of vacant image regions subject to the device resolution and relfectance property of target scene. To solve this problem, a novel depth image completion algorithm was investigated in this paper. To preserve sharp edges in the depth image, an edge mask was ifrst designed. With reference to the edge mask, an improved joint bilateral ifltering scheme was proposed. By ifltering the depth image in four directions, a Markov random ifeld model was used to combine the ifltered depth images into one. Different from conventional filter-based image completion algorithms, the scene occlusion problem is also considered in the proposed algorithm. A variety of depth images are used in the experiment. Comparative results are presented to demonstrate the improvement over some classical methods.