Publications

Liu, YK; Long, TF; Jiao, WL; Chen, B; Cheng, B; Du, YH; He, GJ; Huang, P (2023). Leveraging NightDay Calibration Data to Correct Stripe Noise and Vignetting in SDGSAT-1 Nighttime-Light Images. IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 61, 5616923.

Abstract
The challenge of performing relative radiometric correction on raw nighttime-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 article 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. The novel calibration data called Night orbital data were introduced for vignetting correction. The Night orbital data feature 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 the 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.

DOI:
10.1109/TGRS.2023.3300257

ISSN:
1558-0644