Image stitching of multi-lens with large visual field in range instrumentation

SHENG Lei

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Image stitching of multi-lens with large visual field in range instrumentation

Article | 更新时间：2020-08-13

- Image stitching of multi-lens with large visual field in range instrumentation
- Optics and Precision Engineering Vol. 16, Issue 11, Pages: 2145-2150(2008)
- 作者机构：
  
  中科院长春光机所
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP394.1
- Received：24 July 2008，
  
  Revised：18 August 2008，
  
  Published Online：25 November 2008，
  
  Published：25 November 2008
- 稿件说明：
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盛磊. 靶场测量中多镜头大视场视频图像拼接[J]. 光学精密工程, 2008,16(11):2145-2150

SHENG Lei. Image stitching of multi-lens with large visual field in range instrumentation[J]. Optics and precision engineering, 2008, 16(11): 2145-2150.
盛磊. 靶场测量中多镜头大视场视频图像拼接[J]. 光学精密工程, 2008,16(11):2145-2150 DOI：

SHENG Lei. Image stitching of multi-lens with large visual field in range instrumentation[J]. Optics and precision engineering, 2008, 16(11): 2145-2150. DOI：

摘要

目的：为了得到靶场测量中需要的大视场全景视频图像，建立了多镜头大视场视频图像自动拼接系统，对该系统所采用的图像匹配、标记重叠区、无缝拼接等算法进行研究。方法：首先，介绍小波变换和小波包原理。接着，分析了根据小波系数进行匹配的小波变换图像匹配算法。然后，分析了比较旋转标记重叠区算法

即先匹配出多个拟重叠区，旋转后再做匹配计算，进而标记出唯一重叠区。最后分析了基于小波包变换的图像无缝拼接算法，即对图像作小波包变换，按频率融合小波系数

再根据这些系数恢复图像。结果：实验结果表明：本系统将四个 1.1°×0.88°的视场拼接得到一个大约3.3°×1.76°的大视场

拼接图像平滑无明显裂缝

处理速度可达10帧/s。结论：基本满足了靶场测量中大视场视频图像的需求。

Abstract

Objective: In order to get the video image with large visual field in range instrumentation

a system of auto-stitching multi-lens image with large visual field is established and its applied algorithms such as image matching

marking the area of lapping

seamless stitching and etc is investigated. Method: First

the theory of wavelet transformation and wavelet-packet are presented. The image-matching algorithm based on wavelet-transformation by matching wavelet parameters of image is analyzed. Then

marking the area of lapping by comparing and rotating algorithm is analyzed

marking the only lapping area by matching the sub-lapping areas after rotating. Finally

the image seamless stitching algorithm by wavelet-packet transformation is analyzed: after image wavelet-packet transformation

merging the wave-let parameters by frequency and then using the result to rebuild the image. Result: Experimental results indicate that the system gets an image with 3.3°×1.76°large visual field by stitching four image with 1.1°×0.88° visual field

the image after stitching is smooth and seamless

the speed of the system can reach 10F/S. Conclusion: It can satisfy the range instrumentation requirements of getting image with large visual field.

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