基于块匹配的特征级亚像素对齐的广义闭式公式
Generalized Closed-form Formulae for Feature-based Subpixel Alignment in Patch-based Matching
AI总结：
针对基于代价的图像块匹配中亚像素视差计算精度与效率的平衡问题，本文推导了一维匹配下NCC、SSD、SAD代价函数的亚像素视差闭式公式，并推广至高维搜索空间，实验验证其在二维场景下相比现有方法有显著精度提升。
摘要：
基于代价的图像块匹配是计算机视觉、摄影测量和遥感领域各类技术的核心。当需要获取源图像与目标图像中参考块之间的亚像素视差时，必须对代价函数或目标图像进行插值。虽然基于代价的插值最容易实现，但多项研究表明，基于图像的插值能够提升亚像素匹配的精度，但通常需要付出高昂的搜索流程计算成本。这一问题在立体匹配、光流计算等计算密集型应用中尤为突出。本文证明，在一维匹配场景下（例如搜索空间为一维的校正立体图像场景），使用标准NCC（归一化互相关）、SSD（平方差之和）和SAD（绝对差之和）代价函数时，存在亚像素视差计算的闭式公式。随后我们演示了如何将所提出的公式推广到高维搜索空间场景，这类场景是非校正立体匹配和光流提取所必需的。我们还将所得结果与传统的代价体插值公式以及当前最优的基于代价的优化方法进行了对比，结果表明，在一维搜索空间场景下，所提出的公式相比当前最优的基于代价的方法有小幅提升，而在二维搜索空间场景下则有显著提升。
英文摘要：
Cost-based image patch matching is at the core of various techniques in computer vision, photogrammetry and remote sensing. When the subpixel disparity between the reference patch in the source and target images is required, either the cost function or the target image have to be interpolated. While cost-based interpolation is the easiest to implement, multiple works have shown that image based interpolation can increase the accuracy of the subpixel matching, but usually at the cost of expensive search procedures. This, however, is problematic, especially for very computation intensive applications such as stereo matching or optical flow computation. In this paper, we show that closed form formulae for subpixel disparity computation for the case of one dimensional matching, e.g., in the case of rectified stereo images where the search space is of one dimension, exists when using the standard NCC, SSD and SAD cost functions. We then demonstrate how to generalize the proposed formulae to the case of high dimensional search spaces, which is required for unrectified stereo matching and optical flow extraction. We also compare our results with traditional cost volume interpolation formulae as well as with state-of-the-art cost-based refinement methods, and show that the proposed formulae bring a small improvement over the state-of-the-art cost-based methods in the case of one dimensional search spaces, and a significant improvement when the search space is two dimensional.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
