Efficient radiometric triangulation for aerial image consistency across inter and intra variances

In this paper, we present a novel approach to radiometric normalization for aerial images, effectively addressing both intra- and inter-image color and illumination inconsistencies caused by varying sensor technologies, atmospheric conditions, and ground reflection. We introduce a comprehensive mathematical model for radiance transfer, which addresses brightness inhomogeneities resulting from the Bidirectional Reflectance Distribution Function (BRDF) effect and vignetting effect, alongside color inconsistencies due to atmospheric and illumination variations. To enhance the model's efficiency and stability for solutions, we employ a strategy that leverages multiple polynomial models for approximation, significantly simplifying the complexity of rigorous solutions. Our efficient and robust solution leverages advanced radiometric triangulation theories, enabling effective radiometric normalization of aerial images. We validate the efficacy of our method with extensive testing on three large datasets, each containing over two hundred aerial images. The experimental results showcase our method's superiority over state-of-the-art methods, as evidenced by enhanced visual quality and improved quantitative performance in statistical assessments.