加权最小二乘滤波器在FPGA上提高深度图质量

Renzhi Mao, Kaijie Wei, H. Amano, Yukinori Kuno, M. Arai
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引用次数: 0

摘要

基于测量物体与相机之间距离的技术近年来取得了很大进展。通过这一技术,该系统用于三维成像将为人们的生活提供极大的便利。在这个项目中,我们专注于为汽车上的3D场景显示系统优化具有更好质量的深度图。在三维成像过程中,为了计算某一位置与场景中某一特定点之间的距离,它会从两幅图像中计算出两幅深度图,作为三维成像处理的中间产品。然而,存在大量无法测量距离的无效像素。在处理这些缺点时,引入了后滤波作为解决方案。在这个项目中,我们提出在FPGA上实现加权最小二乘(WLS)滤波器,它可以利用相邻像素的结果来填充无效像素。通过我们的方法,可以提高M-KUBOS上深度图的质量。此外,优化后的内存使用可以成功地适应片上内存的大小,并且与ARM内核相比加速了69.29%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weight Least Square Filter for Improving the Quality of Depth Map on FPGA
The techniques based on measuring the distance between objects and the camera itself have made progress in recent years. Through this technology, the system used for 3D imaging will provide a great convenience for people’s lives. In this project, we focus on optimizing depth maps with better quality for the 3D scene display system on the car. During the 3D imaging process, to calculate the distance between a certain location and one of the specific points of the scene, it will produce two depth maps computed from two images as an intermediate product for 3D imaging processing. However, there is a great number of invalid pixels that distance cannot be measured. In dealing with such drawbacks, post-filtering has been introduced as a solution. In this project, we propose implementing the Weight Least Square (WLS) filter on FPGA, which can fill the invalid pixels by using the results of neighboring pixels. Through our approach, we can improve the quality of the depth map on M-KUBOS. Besides that, the optimized memory usage can successfully suit the size of the memory on-chip, and a 69.29% acceleration compared to the ARM core.
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