计算机应用 ›› 2014, Vol. 34 ›› Issue (9): 2673-2677.DOI: 10.11772/j.issn.1001-9081.2014.09.2673

• 虚拟现实与数字媒体 • 上一篇    下一篇

一种适于移动设备的全景图快速拼接方法

戴华阳,冉飞鹏   

  1. 中国矿业大学(北京) 地球科学与测绘工程学院,北京 100083
  • 收稿日期:2014-04-08 修回日期:2014-05-29 出版日期:2014-09-01 发布日期:2014-09-30
  • 通讯作者: 冉飞鹏
  • 作者简介: 
    戴华阳(1964-),男,湖南湘阴人,教授,博士,主要研究方向:“三下”采煤、大地测量学;
    冉飞鹏(1985-),男,甘肃庆阳人,博士研究生,主要研究方向:虚拟漫游、数字城市。
  • 基金资助:

    博士学科点专项科研基金项目;中央高校基本科研业务费专项资金资助项目

Fast panorama stitching algorithm adaptive for mobile devices

DAI Huayang,RAN Feipeng   

  1. College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
  • Received:2014-04-08 Revised:2014-05-29 Online:2014-09-01 Published:2014-09-30
  • Contact: RAN Feipeng
  • Supported by:

    Special Research Found for the Doctoral Program of Higher Education

摘要:

针对传统移动端全景图生成方法存在拼接速度慢、消耗内存以及存在接缝和“鬼影”等问题,提出了一种适用于移动设备的全景图生成算法。算法首先对源序列图像进行色彩校正,从而保证色彩及亮度均匀,以缩短后期图像融合时间;然后在全景图拼接过程中检测“鬼影”,同时运用梯度域目标移除和区域填充方法移除“鬼影”,利用泊松融合进行拼接后的平滑处理;同时在图像拼接过程中优化了内存分配机制,以减少在图像拼接过程中的内存消耗。通过编程实现了该算法,在配置为332MHz处理器和128MB内存的手机上对不同光照下拍摄的分辨率为1280×720的照片进行测试,并与传统的全局全景图拼接算法进行对比,若利用全局全景图拼接算法对2至9张源序列图像进行拼接,内存消耗为12.3~23.6MB,而提出的算法占用更少内存,分别为9.9~14.5MB。实验结果表明该方法消除图像接缝及“鬼影”较彻底,拼接速度快且节省内存,生成的最终全景图质量较好,可用于移动设备上的全景图拼接。

Abstract:

A new panorama generation algorithm for mobile devices was proposed to solve the problem of low stitching speed, more memory consumption, chromatic aberration and ghosting. First, the color correction was performed on source image sequences to balance color and luminance between adjacent images. Then ghosting artifacts were detected when stitching panorama. If a ghosting artifact was found, the corresponding object in the source image would be located, and a gradient domain object removing and region filling operation would be applied to remove the moving object. In addition, Poisson blending was used to further smoothen color transitions and hide visible seams. The time of Poisson blending was greatly reduced after color correction, and a unique memory allocation mechanism was also applied during image stitching process to decrease memory consumption. Finally, the method was tested on a mobile phone with configuration of 332MHz processor and 128MB memory by taking photos of resolution of 1280×720 under different illumination conditions, and compared with the traditional global panorama stitching algorithm by stitching 2 to 9 original sequential images, the memory consumption of global panorama stitching algorithm was from 12.3MB to 23.6MB, while the proposed method took up less memory, only from 9.9MB to 14.5MB. The experimental results show that this method eliminates image seams and "ghost" effect more thoroughly with high mosaic speed and low memory consumption, and the quality of generated panoramic images is better, thus it can be used on mobile devices for panoramic image generation.

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