图像四周暗角
像素
计算机科学
人工智能
辐射定标
校准
噪音(视频)
遥感
计算机视觉
错误检测和纠正
光学
数学
物理
图像(数学)
算法
地质学
统计
镜头(地质)
作者
Yongkun Liu,Tengfei Long,Weili Jiao,Bo Chen,Bo Cheng,Yihong Du,Guojin He,Peng Huang
标识
DOI:10.1109/tgrs.2023.3300257
摘要
The challenge of performing relative radiometric correction on raw Night-Time-Light (NTL) images captured by the Glimmer Image for Urbanization (GIU) sensor of the SDGSAT-1 satellite is the presence of stripe noise and vignetting. To address this issue, this paper presents a universal method for relative radiometric correction of NTL images captured by the push-broom system. A new automated approach to NTL pixel identification based on Gray-level Co-occurrence Matrix (GLCM) was developed to mask NTL ground object pixels from stripe noise, allowing for the calculation of credible stripe noise thresholds. A novel calibration data called "Night-Day" orbital data was introduced for vignetting correction. The "Night-Day" orbital data features an abnormal transition zone that can be used to determine the vignetting correction parameters. The stripe noise thresholds and vignetting correction parameters can be applied to other raw orbital images. Experiments were conducted on raw images from different dates to verify the universality and robustness of the method, and the results were found to be superior to existing methods. A comparison was also made between the calibrated images and original official Level-1 products, with the results indicating that the correction parameters calculated by the proposed method resolve the defects in the original Level-1 products. The correction parameters have been accepted by the official and have been used to update the original GIU Level-1 products. Finally, the results of relative radiometric correction on raw images from around the world further demonstrate the universality and credibility of the correction parameters.
科研通智能强力驱动
Strongly Powered by AbleSci AI