Currently, the networked collaborative observation technology using multi-platform optical payloads for Earth observation (EO) has matured significantly, enabling highly efficient and frequent monitoring of regions of interest. However, substantial radiometric inconsistencies persist among multi-source EO data acquired by networked platform payloads over identical ground target, primarily due to variations in acquisition time, observation geometry, and atmospheric conditions. These discrepancies result in disparate visual effects that severely constrain subsequent data applications. This study focuses on high-resolution visible images, systematically investigates a radiometric consistency processing framework for multi-platform time-series images, and innovatively proposes a radiometric consistency correction method that integrates radioactive transfer theory with nonparametric regression analysis. In this methodology, a top-of-atmosphere (TOA) reflectance model of stable target is used to perform multi-observation parameter conversion, effectively achieving inter-platform radiometric recalibration and TOA radiometric difference correction. Furthermore, after eliminating atmospheric effect and correcting Bidirectional Reflectance Distribution Function (BRDF), we fully exploit the bottom-of-atmosphere (BOA) radiation information from the overlapping areas of the images observed by payloads onboard different EO platforms, so as to establish radiometric connection relationships, and develop a local weighted regression-based (Locally Estimated Scatterplot Smoothing, LOESS) radiometric consistency correction method, successfully addressing the challenge of radiation value inconsistency in multi-temporal images. Validation experiments using multi-temporal high-resolution camera imagery demonstrate that the proposed radiometric consistency correction method significantly enhances radiometric consistency across those images observed by sensors onboard different EO platforms. This advancement substantially promotes the synergistic application of multi-source remote sensing data towards more sophisticated levels.
Zhao Weiwei
,
Wang Yan
,
Qu Xiaofei
,
Li Wan
,
Gao Caixia
,
Ma Lingling
. A radiometric consistency correction method combining radioactive transformation and nonparametric regression for multi-platform optical payload[J]. Journal of University of Chinese Academy of Sciences, 0
: 2025110501
-2025110501
.
DOI: 10.7523/j.ucas. 2025.050
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