电子学报 ›› 2015, Vol. 43 ›› Issue (11): 2200-2209.DOI: 10.3969/j.issn.0372-2112.2015.11.010

• 学术论文 • 上一篇    下一篇

基于图像局部结构的区域匹配变分光流算法

陈震1,2, 张聪炫1,2, 晏文敬1, 吴燕平1   

  1. 1. 南昌航空大学测试与光电工程学院, 江西 南昌 330063;
    2. 无损检测技术教育部重点实验室, 江西 南昌 330063
  • 收稿日期:2014-05-23 修回日期:2014-10-16 出版日期:2015-11-25
    • 通讯作者:
    • 陈震
    • 作者简介:
    • 张聪炫 男,1984年7月出生,河南焦作人.分别于2007年、2014年在南昌航空大学和南京航空航天大学获得学士、博士学位.现为南昌航空大学讲师,硕士生导师,主要研究方向为图像检测与智能识别.E-mail:zcxdsg@163.com
    • 基金资助:
    • 国家自然科学基金 (No.U1233125,No.61462062,No.61401190); 江西省主要学科学术带头人培养计划项目 (No.201208421); 江西省自然科学基金重点项目 (No.20133ACB20004); 江西省科技落地计划项目 (No.201408083); 航空科学基金 (No.11ZC56003,No.2013ZC56005); 江西省自然科学基金 (No.20114BAB201044)

Region Matching Variational Optical Flow Algorithm Based on Image Local Structure

CHEN Zhen1,2, ZHANG Cong-xuan1,2, YAN Wen-jing1, WU Yan-ping1   

  1. 1. School of Measuring and Optical Engineering, Nanchang Hangkong University, Nanchang, Jiangxi 330063 China;
    2. Key Laboratory of Nondestructive Testing, Ministry of Education, Nanchang, Jiangxi 330063 China
  • Received:2014-05-23 Revised:2014-10-16 Online:2015-11-25 Published:2015-11-25
    • Supported by:
    • National Natural Science Foundation of China (No.U1233125, No.61462062, No.61401190); Key Disciplines Academic Leader Cultivation Plan of Jiangxi Province (No.201208421); Key Program of Natural Science Foundation of Jiangxi Province,  China (No.20133ACB20004); and Technology Program of Jiangxi Province (No.201408083); Aeronautical Science Foundation of China, ASFC (No.11ZC56003, No.2013ZC56005); Natural Science Foundation of Jiangxi Province,  China (No.20114BAB201044)

摘要:

针对变分光流算法的计算精度与鲁棒性问题,提出一种基于图像局部结构的区域匹配变分光流算法.光流估计能量泛函的数据项采用图像结构守恒与灰度守恒相结合,并引入规则化非平方惩罚函数,保证了光流估计的精度与鲁棒性;平滑项采用随图像局部结构自适应变化的扩散策略结合区域匹配约束函数能够有效地保护运动物体或场景的边缘轮廓信息;在光流计算过程中引入金字塔分层细化策略克服图像序列中大位移运动引起的像素点漂移现象,并采用数学方法证明光流估计模型的鲁棒性和收敛性.多组实验表明,本文方法在图像中存在剧烈光照变化、非刚性物体复杂运动以及多目标大位移运动等情况下具有较高的计算精度、较好的鲁棒性.

关键词: 变分光流, 图像局部结构, 自适应扩散, 区域匹配

Abstract:

A region matching variational optical flow algorithm based on image local structure according to the computing accuracy and robustness of the variational optical flow method is proposed.Firstly,the data term of the optical flow estimation energy function combines the constancy of the image structure and constancy of the grey value,which introduces a penalty function to ensure the good accuracy and robustness of the optical flow computing.Secondly,the smoothing term uses an adaptive nonlinear diffusion function which related to the image structure to preserve the boundaries of the motion.Finally,the region matching strategy and the coarse-to-fine method are used to compute the large displacement optical flow,and then the robustness and convergence are proved by mathematical method.Several experiments prove that the proposed algorithm has the better precisionand robustness even there are terrible illumination changes,complex motion of non-rigid object and large displacement of multiple objects.

Key words: variational optical flow, image local structure, adaptive diffusion, region matching

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