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Algorithm and VLSI Architecture Co-Design on Efficient Semi-Global Stereo Matching

机译:高效半全局立体声匹配的算法和VLSI架构共同设计

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Semi-global matching (SGM) is favored for high accuracy real-time stereo matching design as it achieves a good trade-off between disparity image quality and computational complexity. Nevertheless, most of previous SGM designs so far are restricted to the real-time processing of small image resolution and disparity range, or achieve high throughput by simplifying the original algorithm at the penalty of significant disparity image quality degradation. We analyze that the major challenge to efficient SGM design is its memory architecture, including both on-chip memory cost and off-chip memory bandwidth. We address the memory architecture challenge by algorithm and architecture co-design. Based on two observed features of SGM algorithm, i.e. incompleteness and inaccuracy, this paper proposes several efficient techniques to reduce on-chip memory cost and compress off-chip memory bandwidth respectively. Moreover, we also design high throughput and pipelined architecture to implement the proposed techniques. The disparity image quality and hardware efficiency of the proposed SGM design are evaluated on both KITTI2015 and Middlebury V3 stereo datasets. Evaluation results demonstrate that, the throughput of the proposed circuit designs can easily achieve 1080P@30fps at the disparity range of 128, and can reduce the on-chip memory cost and off-chip memory bandwidth by up to $4imes $ and $2imes $ respectively while achieving better or the same disparity image quality, compared with the best reference design techniques.
机译:半全局匹配(SGM)有利于高精度实时立体声匹配设计,因为它在差异图像质量和计算复杂性之间实现了良好的权衡。然而,以前的大多数SGM设计到目前为止仅限于小图像分辨率和视差范围的实时处理,或者通过在显着的差异图像质量劣化的惩罚处简化原始算法来实现高吞吐量。我们分析了高效SGM设计的主要挑战是其内存架构,包括片上内存成本和片外存储器带宽。我们通过算法和架构共同设计解决内存架构挑战。基于SGM算法的两个观察到的特征,即不完备和不准确性,本文提出了几种有效的技术来减少片上存储器成本并分别压缩片外存储带宽。此外,我们还设计了高吞吐量和流水线架构,以实现所提出的技术。在Kitti2015和Middenbury V3立体声数据集中评估所提出的SGM设计的差异图像质量和硬件效率。评估结果表明,所提出的电路设计的吞吐量可以在128的视差范围内容易地实现1080p @ 30fps,并且可以通过最多减少片上内存成本和片内存存储带宽<内联公式XMLNS:MML =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999/xlink”> $ 4 次$ 和<内联公式XMLNS:MML =“http://www.w3.org/1998/math/mathml”xmlns:xlink =“http://www.w3.org/1999/xlink”> $ 2 次$ 分别在实现更好或相同的视差图像质量的同时,与最佳参考设计技术相比。

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