提升卫星影像拼接精度,实现印度全域100米级高保真影像图。
Geometric Correction and Mosaic Generation of Geo High Resolution Camera Images
- 基于几何校正与图像追踪算法,解决多帧拼接误差问题。
- 通过在轨标定,定位精度显著提升,支持100米分辨率地图生成。
- 适合遥感监测、环境评估等需要高精度影像的用户。
搭载于印度空间研究组织GSAT-29卫星的地理高分辨率相机(GHRC)是运行在东经55度地球静止轨道上的六波段可见光与近红外成像仪,其星下点地面分辨率为55米,单次成像覆盖110×110公里区域,可通过扫描镜机制观测整个地球圆盘。为覆盖印度地区,GHRC采用二维光栅扫描方式,产生超过1,000幅影像,需拼接为无缝全景图。本文提出地物定位模型,分析定位误差来源,并评估定位精度。针对波段间配准与帧间拼接难题,开发了几何校正、波段对齐及无缝拼接算法。通过在轨几何标定,利用地面参考图像调整仪器内部姿态角,显著提升了指向与定位精度。进一步提出回溯算法,结合几何模型、图像处理与空间后方交会技术,修正大尺度拼接中的帧间误差。上述改进已实现印度全域100米分辨率、高几何保真的业务化影像拼接,大幅增强GHRC在地球观测与监测中的应用能力。
原文摘要 · Abstract (English)
The Geo High Resolution Camera (GHRC) aboard ISRO GSAT-29 satellite is a state-of-the-art 6-band Visible and Near Infrared (VNIR) imager in geostationary orbit at 55degE longitude. It provides a ground sampling distance of 55 meters at nadir, covering 110x110 km at a time, and can image the entire Earth disk using a scan mirror mechanism. To cover India, GHRC uses a two-dimensional raster scanning technique, resulting in over 1,000 scenes that must be stitched into a seamless mosaic. This paper presents the geolocation model and examines potential sources of targeting error, with an assessment of location accuracy. Challenges in inter-band registration and inter-frame mosaicing are addressed through algorithms for geometric correction, band-to-band registration, and seamless mosaic generation. In-flight geometric calibration, including adjustments to the instrument interior alignment angles using ground reference images, has improved pointing and location accuracy. A backtracking algorithm has been developed to correct frame-to-frame mosaicing errors for large-scale mosaics, leveraging geometric models, image processing, and space resection techniques. These advancements now enable the operational generation of full India mosaics with 100-meter resolution and high geometric fidelity, enhancing the GHRC capabilities for Earth observation and monitoring applications.
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