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Relative radiometric normalization (RRN) mosaicking among multiple remotesensing images is crucial for the downstream tasks, including map-making, imagerecognition, semantic segmentation, and change detection. However, there areoften seam lines on the mosaic boundary and radiometric contrast left,especially in complex scenarios, making the appearance of mosaic imagesunsightly and reducing the accuracy of the latter classification/recognitionalgorithms. This paper renders a novel automatical approach to eliminate seamlines in complex RRN mosaicking scenarios. It utilizes the histogram matchingon the overlap area to alleviate radiometric contrast, Poisson editing toremove the seam lines, and merging procedure to determine the normalizationtransfer order. Our method can handle the mosaicking seam lines with arbitraryshapes and images with extreme topological relationships (with a smallintersection area). These conditions make the main feathering or blendingmethods, e.g., linear weighted blending and Laplacian pyramid blending,unavailable. In the experiment, our approach visually surpasses the automaticmethods without Poisson editing and the manual blurring and feathering methodusing GIMP software.

Automatically eliminating seam lines with Poisson editing in complex relative radiometric normalization mosaicking scenarios