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计算机工程

• 图形图像处理 • 上一篇    下一篇

航空遥感图像拼接算法及其精度评价

杨 彬1,李旭东2,晏 磊1,余优生3   

  1. (1. 北京大学遥感与地理信息系统研究所空间信息集成与3S工程应用北京市重点实验室,北京 100871; 2. 北京航空航天大学精密光机电一体化技术教育部重点实验室,北京 100191;3. 北京星天地信息科技有限公司,北京 100083)
  • 收稿日期:2012-10-11 出版日期:2014-03-15 发布日期:2014-03-13
  • 作者简介:杨 彬(1989-),男,博士研究生,主研方向:摄影测量与遥感;李旭东,副教授、博士;晏 磊,教授、博士;余优生,工程师。
  • 基金资助:
    国家自然科学基金资助项目“内视场拼接相机的数字基高比模型与精度评价机理”(11174017);国家科技支撑计划基金资助项目“大规模航空遥感产业化综合应用示范”(2011BAH12B07)。

Mosaic Algorithm for Aerial Remote Sensing Image and Its Accuracy Evaluation

YANG Bin  1, LI Xu-dong  2, YAN Lei  1, YU You-sheng   3   

  1. (1. Beijing Key Lab of Spatial Information Integration & Its 3S Engineering Applications, Institute of Remote Sensing & Geographic Information System, Peking University, Beijing 100871, China; 2. Key Laboratory of Precision Opto-mechatronics Technology, Ministry of Education, Beihang University, Beijing 100191, China; 3. Beijing XTD Information & Technology Co., Ltd., Beijing 100083, China)
  • Received:2012-10-11 Online:2014-03-15 Published:2014-03-13

摘要: 针对航空遥感成像范围小、视差角大的特点,提出一种航空遥感图像拼接算法。通过估算图像相对方位矩阵,使用透视变换实现图像校正,解决大视差角下的畸变问题。利用SIFT算法和基于概率密度的错误匹配点剔除方法,实现高精度图像配准,并通过小波变换完成图像融合工作。实验结果表明,在不同地表情况下,该算法的拼接性能均优于传统SIFT算法。

关键词: 图像拼接, 航空遥感, 透视变换, 小波变换, 精度评价, 图像校正

Abstract: Small imaging coverage and big parallax angle make aerial remote sensing more difficult to image processing. This paper proposes an algorithm for aerial remote sensing image mosaic. The original image is corrected by perspective transform with estimating matrix which is determined by the relative attitude of two images. It solves the distortion problem caused by big parallax angle. Image registration is approached by the Scale Invariant Feature Transform(SIFT) algorithm and a method based on probability density. The image mosaic process is completed by the wavelet transform. Experimental result shows that the mosaic performance of this algorithm is better than traditional SIFT algorithm in different surface conditions.

Key words: image mosaic, aerial remote sensing, perspective transform, wavelet transform, accuracy evaluation, image correction

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