Suppr超能文献

基于大虚拟相机的高分二号光学遥感卫星双相机系统图像拼接方法

Image Mosaicking Approach for a Double-Camera System in the GaoFen2 Optical Remote Sensing Satellite Based on the Big Virtual Camera.

作者信息

Cheng Yufeng, Jin Shuying, Wang Mi, Zhu Ying, Dong Zhipeng

机构信息

State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.

出版信息

Sensors (Basel). 2017 Jun 20;17(6):1441. doi: 10.3390/s17061441.

Abstract

The linear array push broom imaging mode is widely used for high resolution optical satellites (HROS). Using double-cameras attached by a high-rigidity support along with push broom imaging is one method to enlarge the field of view while ensuring high resolution. High accuracy image mosaicking is the key factor of the geometrical quality of complete stitched satellite imagery. This paper proposes a high accuracy image mosaicking approach based on the big virtual camera (BVC) in the double-camera system on the GaoFen2 optical remote sensing satellite (GF2). A big virtual camera can be built according to the rigorous imaging model of a single camera; then, each single image strip obtained by each TDI-CCD detector can be re-projected to the virtual detector of the big virtual camera coordinate system using forward-projection and backward-projection to obtain the corresponding single virtual image. After an on-orbit calibration and relative orientation, the complete final virtual image can be obtained by stitching the single virtual images together based on their coordinate information on the big virtual detector image plane. The paper subtly uses the concept of the big virtual camera to obtain a stitched image and the corresponding high accuracy rational function model (RFM) for concurrent post processing. Experiments verified that the proposed method can achieve seamless mosaicking while maintaining the geometric accuracy.

摘要

线阵推扫成像模式广泛应用于高分辨率光学卫星(HROS)。使用通过高刚性支架连接的双相机并结合推扫成像,是在确保高分辨率的同时扩大视场的一种方法。高精度图像拼接是完整拼接卫星图像几何质量的关键因素。本文提出了一种基于高分二号光学遥感卫星(GF2)双相机系统中的大虚拟相机(BVC)的高精度图像拼接方法。可以根据单个相机的严格成像模型构建大虚拟相机;然后,通过正投影和反投影将每个TDI-CCD探测器获得的每个单图像条带重新投影到大型虚拟相机坐标系的虚拟探测器上,以获得相应的单虚拟图像。经过在轨校准和相对定向后,基于单个虚拟图像在大型虚拟探测器图像平面上的坐标信息将它们拼接在一起,从而获得完整的最终虚拟图像。本文巧妙地利用大虚拟相机的概念来获得拼接图像以及相应的高精度有理函数模型(RFM),用于同步后处理。实验验证了该方法在保持几何精度的同时能够实现无缝拼接。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/645e/5492188/9f224cf57644/sensors-17-01441-g001.jpg

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验