Registration of moving fuzzy image in high dynamic environment

FU Qiang; SUN Xiu-xia; PENG Ke; LIU Shu-guang

doi:10.3788/OPE.20152313.0523

您当前的位置：

首页 >

文章列表页 >

Registration of moving fuzzy image in high dynamic environment

更新时间：2020-08-13

- Registration of moving fuzzy image in high dynamic environment
- Optics and Precision Engineering Vol. 23, Issue 10z, Pages: 522-527(2015)
- 作者机构：
  
  空军工程大学航空航天工程学院,陕西西安,710038
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152313.0523
  CLC： TP391.4
- Received：20 April 2015，
  
  Revised：28 May 2015，
  
  Published：14 November 2015
- 稿件说明：
移动端阅览
付强, 孙秀霞, 彭轲等. 高动态环境下的运动模糊图像配准[J]. 光学精密工程, 2015,23(10z): 522-527

FU Qiang, SUN Xiu-xia, PENG Ke etc. Registration of moving fuzzy image in high dynamic environment[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 522-527
付强, 孙秀霞, 彭轲等. 高动态环境下的运动模糊图像配准[J]. 光学精密工程, 2015,23(10z): 522-527 DOI： 10.3788/OPE.20152313.0523.

FU Qiang, SUN Xiu-xia, PENG Ke etc. Registration of moving fuzzy image in high dynamic environment[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 522-527 DOI： 10.3788/OPE.20152313.0523.

摘要

由于高动态环境下摄像机拍摄的待配准图像存在大旋转变换的同时还会受运动模糊退化的影响

故本文设计了一种高动态环境下的运动模糊图像配准方法。分析了传统尺度不变特征变换(SIFT)算法实时性差的原因

利用灰度级变换对SIFT算法进行改进

对两幅待配准图像特征点的提取进行简化

从而避开检测出大量无用特征点带来实时性差的问题。然后选取简化后的特征点进行特征匹配

使配准算法精度更高。最后通过实验验证了本文设计方法的实效性。实验结果表明:提出的算法的特征点数以及匹配对数保持在改善算法前的10%以内

大大减少了计算量;该算法对图像旋转的稳定性更强

匹配对数占检测出的特征点数的比值范围从0.1505减小到0.1365。相比SIFT算法效率更高

稳定性更强

更能满足高动态环境下的图像配准要求。

Abstract

In matching the under-registration images in a high dynamic environment

there is large rotation distortion meanwhile the images may turn into blur in motion states

so traditional algorithms fail to match the images accurately in real-time. To solve these problems

a registration algorithm of fuzzy image in the high dynamic environment was designed in this paper. Based on the analysis of the cause of the Scale Invarian Feature Transform(SIFT) algorithm's poor timeliness

the gray-scale transform was chosen as a threshold to change the pixels of image and to reduce the number of feature points. Then

simplified feature points were chosen to implement the feature matching to improve the accuracy of the registration. Finally

an experiment was performed to demonstrate the effectiveness of this method. Experimental results indicate that the number of matching-pairs and feature points are 10% that of the original algorithm; the stability is stronger than that of the original SIFT algorithm

and the ratio of matching-pair and feature points are reduced from 0.1505 to 0.1365. Compared with the traditional SIFT algorithm

this method owns better efficiency and stability

and can satisfy the requirements of image matching in the high dynamic environment.

关键词

Keywords

references

余先川,吕中华,胡丹. 遥感图像配准技术综述[J]. 光学精密工程,2013,21(11):2960-2972. YU X CH, LÜ ZH H, HU D. Review of remote sensing image registration techniques[J]. Opt. Precision Eng., 2013,21(11):2960-2972.(in Chinese)

王健博,朱明. 基于字典描述向量的实时图像配准[J]. 光学精密工程, 2014,22(6):1613-1621. WANG J B, ZHU M. Real time image registration based on dictionary feature descriptor[J].Opt. Precision Eng.,2014,22(6):1613-1621.(in Chinese)

沈同圣,张健,娄树理. 面向目标检测的空间观测图像精确配准[J]. 光学精密工程,2014,22(8):2205-2213. SHEN T SH, ZHANG J, LOU SH L. Precise registration of space observation images for target detection[J]. Opt. Precision Eng.,2014,22(8):2205-2213.(in Chinese)

刘佳,傅卫平,王雯,等. 基于改进SIFT算法的图像匹配[J]. 仪器仪表学报, 2013,34(5):1107-1112. LIU J, FU W P, WANG W, et al.. Image matching based on improved SIFT algorithm[J]. Chinese Journal of Scientific Instrument, 2013,34(5):1107-1112.(in Chinese)

刘辉,申海龙. 一种基于改进SIFT算法的图像配准方法[J]. 微电子学与计算机,2014,31(1):38-42. LIU H, SHEN H L. Image match method based on improved SIFT algorithm[J].Microelectronics and Computer, 2014,31(1):38-42.(in Chinese)

尚明姝. 基于改进SIFT特征匹配的快速图像拼接算法[J]. 微电子学与计算机,2014,31(1):64-67. SHANG M SH. A fast image mosaic algorithm based on improved SIFT feature matching[J]. Microelectronics and Computer, 2014,31(1):64-67.(in Chinese)

齐乃新,曹立佳,杨小冈,等. 基于方向约束的改进SIFT匹配算法[J]. 计算机科学,2014,41(6A):125-128. QI N X, CAO L J, YANG X G, et al.. Improved SIFT matching algorithm based on orientation constraint[J]. Computer Science, 2014,41(6A):125-128.(in Chinese)

张德全,董世存. 改进SIFT算法在图像数据相似性匹配中的应用研究[J]. 计算机科学,2014,41(6A):122-124. ZHANG D Q, DONG SH C. Application research on comparability matching for image-data based on enhanced SIFT algorithm[J]. Computer Science, 2014,41(6A):122-124.(in Chinese)

师艳伟,杨晶东,杨敬辉. 一种改进SIFT 算法[J]. 江南大学学报:自然科学版, 2014,13(4):403-410. SHI Y W, YANG J D, YANG J H. Research on an improved SIFT algorithm[J]. Journal of Jiangnan University:Natural Science Edition, 2014,13(4):403-410(in Chinese)

卢朝梁,马丽华,陈豪. 改进的SIFT特征匹配算法[J]. 空军工程大学学报:自然科学版, 2014,15(1):72-76. LU CH L, MA L H, CHEN H. An improved algorithm for SIFT feature matching[J]. Journal of Air Force Engineering University:Natural Science Edition,2014,15(1):72-76.(in Chinese)

LOWE D G. Distinctive image features from scale-invariant key points[J]. International Journal of Computer Vision,2004,60(2):91-110.

Views

406

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Feature fusion and weight adaptive updating based motion blur object tracking

Blurred star restoration based on improved Radon transform and sparse prior

Identification of robust blur parameter for uniform linear motion blurred images

Restoration of motion blurred image in dual CMOS imaging system

Total variation image restoration for mixed blur in moving image

Related Author

Guang-long WANG

Jie TIAN

Wen-jie ZHU

Dan FANG

Tian-yu ZHENG

WEI Xing-zhu1

CAO Jun2

Related Institution

Laboratory of Nanotechnology and Microsystems, Shijiazhuang Campus, Army Engineering University

Key Laboratory of Infrared System Detection and Imaging Technology, Chinese Academy of Sciences

Shanghai Institute of Technical Physics, Chinese Academy of Sciences

University of Chinese Academy of Sicences

Information and Computer Engineering College, Northeast Forestry University

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰