An Improved On-Orbit Relative Radiometric Calibration Method for Agile High-Resolution Optical Remote-Sensing Satellites With Sensor Geometric Distortion

校准 失真(音乐) 遥感 辐射定标 计算机科学 计算机视觉 探测器 图像传感器 人工智能 激光雷达 视野 卫星 数学 物理 地质学 电信 天文 统计 计算机网络 放大器 带宽(计算)
作者
Litao Li,Guo Zhang,Yonghua Jiang,Xin Shen
出处
期刊:IEEE Transactions on Geoscience and Remote Sensing [Institute of Electrical and Electronics Engineers]
卷期号:60: 1-15 被引量:5
标识
DOI:10.1109/tgrs.2021.3078815
摘要

Noticeable striping artifacts in collected satellite imagery, caused by the inconsistency of pushbroom sensor detector responses, degrade the image quality. Relative radiometric calibration aims to calibrate inconsistencies in terms of detector responses, thereby eliminating detector-level striping artifacts. Yaw calibration has become the preferred imagery-based calibration method for satellites without on-board calibration equipment, owing to its high accuracy and convenience. However, it often relies on a large uniform field on the Earth’s surface and is a linear calibration method. This method does not consider acquisition-related geometric errors associated with the sensor, resulting in reduced calibration accuracy. In this study, we propose an improved method for yaw calibration, which accounts for the geometric distortion of sensor imaging and does not require a uniform field. A fast geometric-positioning algorithm was used to remove geometric distortion, followed by high-precision extraction of the calibration reference for each sensor’s detector. The dynamic range of the sensor calibration was extended, followed by the calibration of the sensor nonlinear response model. Our results based on Yaogan-25 images suggest the following: 1) the improved method effectively eliminates the “sawtooth” caused by the yaw calibration method without considering the geometric distortion and 2) it outperforms other imagery-based calibration methods with respect to visual destriping effects such that the root-mean-square deviations of the corrected imagery experienced a decrease of 0.65 percentage point, compared with that of the statistical method, and 0.17 percentage point for the yaw calibration. Such improvements will promote high-quality applications of remote-sensing images.
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