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Texture Synthesis Repair of RealSense D435i Depth Images with Object-Oriented RGB Image Segmentation

机译:具有面向对象RGB图像分割的RealSense D435i深度图像的纹理综合修复

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摘要

A depth camera is a kind of sensor that can directly collect distance information between an object and the camera. The RealSense D435i is a low-cost depth camera that is currently in widespread use. When collecting data, an RGB image and a depth image are acquired simultaneously. The quality of the RGB image is good, whereas the depth image typically has many holes. In a lot of applications using depth images, these holes can lead to serious problems. In this study, a repair method of depth images was proposed. The depth image is repaired using the texture synthesis algorithm with the RGB image, which is segmented through a multi-scale object-oriented method. The object difference parameter is added to the process of selecting the best sample block. In contrast with previous methods, the experimental results show that the proposed method avoids the error filling of holes, the edge of the filled holes is consistent with the edge of RGB images, and the repair accuracy is better. The root mean square error, peak signal-to-noise ratio, and structural similarity index measure from the repaired depth images and ground-truth image were better than those obtained by two other methods. We believe that the repair of the depth image can improve the effects of depth image applications.
机译:深度相机是一种传感器,可以直接收集物体和相机之间的距离信息。 RealSense D435i是一种低成本的深度相机,目前正在广泛使用。当收集数据时,同时获取RGB图像和深度图像。 RGB图像的质量良好,而深度图像通常具有许多孔。在使用深度图像的大量应用中,这些孔可能导致严重问题。在该研究中,提出了一种深度图像的修复方法。使用具有RGB图像的纹理合成算法修复深度图像,该算法通过多尺度面向对象的方法进行分段。对象差异参数被添加到选择最佳样本块的过程中。与先前的方法相比,实验结果表明,该方法避免了孔的误差填充,填充孔的边缘与RGB图像的边缘一致,修复精度更好。从修复的深度图像和地面图像的根均方误差,峰值信噪比和结构相似性指标措施优于另外两种方法获得的误差。我们认为深度图像的修复可以提高深度图像应用的影响。

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