计算机与现代化 ›› 2022, Vol. 0 ›› Issue (12): 95-101.

• 图像处理 • 上一篇    下一篇

基于GMS和改进最佳缝合线的视差图像拼接算法

  

  1. (1.长沙理工大学物理与电子科学学院,湖南长沙410114; 2.中国人民解放军第3303工厂,湖北武汉430200)
  • 出版日期:2023-01-04 发布日期:2023-01-04
  • 作者简介:李四杰(1996—),男,湖南长沙人,硕士研究生,研究方向:图像处理,阵列信号处理,E-mail: lisijie_st@163.com; 通信作者:唐清善(1977—),男,湖南永州人,讲师,硕士生导师,博士,研究方向:数字信号处理,模式识别,E-mail: cstqs001@126.com; 高英华(1980—),男,湖北武汉人,工程师,研究方向:图像处理。
  • 基金资助:
    长沙理工大学研究生科研创新项目(CX2020SS92)

Parallax Image Stitching Algorithm Based on GMS and Improved Optimal Seam

  1. (1.School of Physics and Electronic Science, Changsha University of Science and Technology, Changsha 410114, China;
    2.No.3303 Factory of the Chinese People’s Liberation Army, Wuhan 430200, China)
  • Online:2023-01-04 Published:2023-01-04

摘要: 针对视差图像拼接时,拼接图像存在鬼影、亮度不均匀等问题,本文提出一种基于网格运动统计(Grid-based Motion Statistics, GMS)和改进最佳缝合线的视差图像拼接算法。算法首先利用快速特征点提取和描述(Oriented FAST and Rotated BRIEF, ORB)算法提取特征点,并采用GMS算法筛除误匹配点;然后引入HSV颜色空间和图像梯度差改进能量函数,避免缝合线穿过图像边缘;最后基于图切割法求取最佳缝合线,进行图像的梯度融合拼接。仿真实验结果表明,在图像存在较大视差的情况下,本文算法特征点匹配正确率较基于尺度特征不变(Scale Invariant Feature Transform, SIFT)算法和基于加速稳健性特征(Speeded Up Robust Features, SURF)算法最低和最高提高了2.01倍和4.73倍,图像自然度平均提高了22.6%,且拼接的图像亮度均匀、无透视畸变。

关键词: 图像处理, 图像拼接, 运动网格统计, 图切割, 最佳缝合线, 梯度融合

Abstract: Aiming at the problems of ghost and uneven brightness in parallax image stitching, this paper proposes a parallax image stitching algorithm based on grid motion statistics(GMS) and improved optimal seam. Firstly, the fast feature extraction and description(ORB) algorithm is used to extract feature points and the GMS algorithm is used to screen out the mismatched points. Then, HSV color space and image gradient difference are introduced to improve the energy function to avoid the stitching line passing through the image edge. Based on the graph cutting method, the optimal seam is obtained, and the gradient fusion stitching of the image is carried out. The simulation results show that, in the case of large disparity, compared with the algorithm based on scale feature invariance(SIFT) and the algorithm based on accelerated robustness feature(SURF), the accuracy of feature point matching of this algorithm is increased by 2.01 times and 4.73 times at the lowest and highest, and the image naturalness is increased by 20.6% on average. Moreover, the stitched image has uniform brightness and no perspective distortion.

Key words: image processing, image stitching, grid-based motion statistics, graph-cut, optimal seam, gradient fusion