Li Li, Yao Jian, Xie Renping, Xia Menghan, Zhang Wei
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China.
School of Control Science and Engineering, Shandong University, Jinan 250061, China.
Sensors (Basel). 2016 Dec 22;17(1):1. doi: 10.3390/s17010001.
In this paper, we propose a unified framework to generate a pleasant and high-quality street-view panorama by stitching multiple panoramic images captured from the cameras mounted on the mobile platform. Our proposed framework is comprised of four major steps: image warping, color correction, optimal seam line detection and image blending. Since the input images are captured without a precisely common projection center from the scenes with the depth differences with respect to the cameras to different extents, such images cannot be precisely aligned in geometry. Therefore, an efficient image warping method based on the dense optical flow field is proposed to greatly suppress the influence of large geometric misalignment at first. Then, to lessen the influence of photometric inconsistencies caused by the illumination variations and different exposure settings, we propose an efficient color correction algorithm via matching extreme points of histograms to greatly decrease color differences between warped images. After that, the optimal seam lines between adjacent input images are detected via the graph cut energy minimization framework. At last, the Laplacian pyramid blending algorithm is applied to further eliminate the stitching artifacts along the optimal seam lines. Experimental results on a large set of challenging street-view panoramic images captured form the real world illustrate that the proposed system is capable of creating high-quality panoramas.
在本文中，我们提出了一个统一的框架，通过拼接从安装在移动平台上的相机捕获的多个全景图像来生成令人愉悦且高质量的街景全景图。我们提出的框架由四个主要步骤组成：图像扭曲、颜色校正、最优接缝线检测和图像融合。由于输入图像是从相对于相机存在不同程度深度差异的场景中捕获的，没有精确的公共投影中心，因此这些图像在几何上无法精确对齐。因此，首先提出了一种基于密集光流场的高效图像扭曲方法，以极大地抑制大几何错位的影响。然后，为了减轻由光照变化和不同曝光设置引起的光度不一致的影响，我们提出了一种通过匹配直方图极值点的高效颜色校正算法，以大幅减少扭曲图像之间的颜色差异。之后，通过图割能量最小化框架检测相邻输入图像之间的最优接缝线。最后，应用拉普拉斯金字塔融合算法进一步消除沿最优接缝线的拼接伪影。在从现实世界捕获的大量具有挑战性的街景全景图像上的实验结果表明，所提出的系统能够创建高质量的全景图。
