Improved BRISK algorithm used in image mosaic

CHEN Si-cong; LIU Jing-hong; HE Lin-yang; ZHOU Qian-fei

doi:10.3788/YJYXS20163103.0324

您当前的位置：

首页 >

文章列表页 >

Improved BRISK algorithm used in image mosaic

Display and Image | 更新时间：2020-08-12

- Improved BRISK algorithm used in image mosaic
- Chinese Journal of Liquid Crystals and Displays Vol. 31, Issue 3, Pages: 324-330(2016)
- 作者机构：
  
  1. 中国科学院大学北京,中国,100049
  2. 中国科学院长春光学精密机械与物理研究所航空光学成像与测量重点实验室,吉林长春,130033
- 作者简介：
- 基金信息：
- DOI：10.3788/YJYXS20163103.0324
  CLC： TP722
- Received：17 February 2015，
  
  Revised：22 June 2015，
  
  Published：05 March 2016
- 稿件说明：
移动端阅览
陈思聪, 刘晶红, 何林阳等. 一种用于图像拼接的改进BRISK算法[J]. 液晶与显示, 2016,31(3): 324-330

CHEN Si-cong, LIU Jing-hong, HE Lin-yang etc. Improved BRISK algorithm used in image mosaic[J]. , 2016,31(3): 324-330
陈思聪, 刘晶红, 何林阳等. 一种用于图像拼接的改进BRISK算法[J]. 液晶与显示, 2016,31(3): 324-330 DOI： 10.3788/YJYXS20163103.0324.

CHEN Si-cong, LIU Jing-hong, HE Lin-yang etc. Improved BRISK algorithm used in image mosaic[J]. , 2016,31(3): 324-330 DOI： 10.3788/YJYXS20163103.0324.

摘要

为了获得精准的航空拼接图像

本文提出了一种结合BRISK算法与互相关模块匹配算法的新算法。传统的BRISK算法在拼接平移方向上存在较大的误差。针对该问题

首先使用BRISK算法实现尺度和旋转的校正

再引入模块匹配方法完成平移校正

同时在BRISK算法中加入RANSANC算法实现精准拼接。实验结果表明

本文算法是一种运算时间短、精确度高、拼接效果良好的图像拼接方法。

Abstract

In order to obtain accurate aerial stitching images

a new algorithm combined with Binary Robust Invariant Scalable Keypoints (BRISK) and cross-correlation template matching algorithm is proposed in this thesis. There are some errors in the splicing translational direction on using traditional BRISK algorithm in image mosaic. Aiming at the problem

the BRISK algorithm is firstly used for the scale and rotation correction of the matching images. Then the template matching method is used for the translation correction. Meanwhile

the random sample consensus (RANSANC) algorithm is added to the BRISK algorithm to achieve precise mosaic. The experiment results show that the proposed algorithm has short operation time

high precision

and can achieve good image mosaic results.

关键词

Keywords

references

郭晓冉,崔少辉.基于局部特征点配准的图像拼接算法[J].半导体光电,2014,35(1):89-94. GUO X R, CUI S H. Image mosaic approach using local feature points registration[J]. Semiconductor Optoelectronics, 2014, 35(1):89-94. (in Chinese)

张琳,褚龙现.基于全局拼接的航拍图像拼接算法研究[J].计算机仿真,2012,29(4):282-285,300. ZHANG L, CHU L X. Aerial image mosaic algorithms research based on global mosaic[J]. Computer Simulation, 2012, 29(4):282-285, 300. (in Chinese)

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):2960-2968. YU X C, LV Z H, HU D. Review of remote sensing image registration techniques[J]. Opt. Precision Eng., 2013, 21(11):2960-2968. (in Chinese)

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

CALONDER M, LEPETIT V, STRECHA C, et al. BRIEF:Binary robust independent elementary features[C]. Proceedings of the European Conference on Computer Vision, Berlin Heidelberg:Springer, 2010:778-792.

LEUTENEGGER S, CHLI M, SIEGWART R Y. BRISK:Binary robust invariant scalable keypoints[C]. Proceedings of the IEEE International Conference on Computer Vision, Washington, DC, USA:IEEE, 2011:2548-2555.

TAKACS G, CHANDRASEKHAR V, TSAI S, et al. Rotation-invariant fast features for large-scale recognition and real-time tracking[J]. Signal Processing:Image Communication, 2013, 28(4):334-344.

王灿进,孙涛,陈娟.局部不变特征匹配的并行加速技术研究[J].液晶与显示,2014,29(2):266-274. WANG C J, SUN T, CHEN J. Speeding up local invariant feature matching using parallel technology[J]. Chinese Journal of Liquid Crystals and Displays, 2014, 29(2):266-274. (in Chinese)

张志纯,况立群,韩燮,等.一种改进的RANSAC图像拼接算法[J].计算机测量与控制,2014,22(6):1856-1858. ZHANG Z C, KUANG L Q, HAN X, et al. An improved RANSAC algorithm for image mosaic[J]. Computer Measurement & Control, 2014, 22(6):1856-1858. (in Chinese)

刘忠红,储珺.特征提取与模板匹配结合的图像拼接方法[J].微计算机信息,2010,26(1-1):117-118,156. LIU Z H, CHU J. A method for image mosaic based on combining feature extraction with template matching[J]. Microcomputer Information, 2010, 26(1-1):117-118, 156. (in Chinese)

SAHANI S K, ADHIKARI G, DAS B K. A fast template matching algorithm for aerial object tracking[C]. 2011 International Conference on Image Information Processing, Himachal Pradesh:IEEE, 2011:1-6.

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

OpenMV-based intelligent "find" trolley control system

Screw counting method based on image processing

Blood image recognition system based on DSP

Real-Time Image Mosaic Technology Based on DSP

Defects Detection Technology of VFD Display Image

Related Author

Cheng-yong LI

Han-zhong TAN

Sha WANG

Jing-jing HU

Jiao-jiao MIAO

Yi-min LIU

LUO Gang-yin

WANG Bi-dou

Related Institution

School of Electronic Information, Chongqing Institute of Engineering

College of Information Science and Engineering, Wuhan University of Science and Technology

CAS Key Lab of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences

Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China

Institute of Electronics and Electrical Engineering, Nanyang Institute of Technology

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China 130033 Postal code：130033
Tel：0431-86176059 Email：yjxs@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