  Relative radiometric normalization (RRN) mosaicking among multiple remote
sensing images is crucial for the downstream tasks, including map-making, image
recognition, semantic segmentation, and change detection. However, there are
often seam lines on the mosaic boundary and radiometric contrast left,
especially in complex scenarios, making the appearance of mosaic images
unsightly and reducing the accuracy of the latter classification/recognition
algorithms. This paper renders a novel automatical approach to eliminate seam
lines in complex RRN mosaicking scenarios. It utilizes the histogram matching
on the overlap area to alleviate radiometric contrast, Poisson editing to
remove the seam lines, and merging procedure to determine the normalization
transfer order. Our method can handle the mosaicking seam lines with arbitrary
shapes and images with extreme topological relationships (with a small
intersection area). These conditions make the main feathering or blending
methods, e.g., linear weighted blending and Laplacian pyramid blending,
unavailable. In the experiment, our approach visually surpasses the automatic
methods without Poisson editing and the manual blurring and feathering method
using GIMP software.
