LAUSR

Radiometric normalization (RN) minimizes the radiometric inconsistencies between images in synthetic aperture radar (SAR) mosaic images. However, the radiometric principle of SAR has not been fully considered by the existing methods. To this issue, a radiometric-principle-based RN (RPRN) method is proposed. First, image areas with consistent coverage areas in object space and approximate rough ground surface between images are extracted as adjustment candidates based on the imaging principle. Then, considering the radiometric characteristic of SAR image, all the images are taken as a whole to solve the radiometric adjustment model, which transfers RN into the least-square optimization. Finally, a global quantization strategy is used to ensure radiometric consistency during orthorectification and mosaicking. The experimental results of Gaofen-3 SAR images demonstrate that the proposed method has the best performance and can effectively and stably eliminate the radiometric differences between images.