Orthoimage mosaicking plays an important role in remote sensing applications, such as environment monitoring and protection. However, the cloud coverage in remote sensing images often results in substantial loss of information and degradation of data quality, bringing lots of challenges to orthoimage mosaicking. Therefore, this paper proposes a flexible multi-temporal orthoimage mosaicking method based on dynamic variable patches. Different from most existing pixel-based mosaicking methods, the proposed method defines patch as the minimal processing unit for orthoimage mosaicking, and the size and position of each patch are dynamic variable. Patches from different images are rearranged under the image texture consistency constraint to generate the mosaic image. In the proposed method, the initial positions of available patches of all images are determined first, then the initial size of each patch is determined by the cloud coverage and the effective area of image. Subsequently, considering the inevitable misalignments between different orthoimages, the texture similarity between patches is utilized to select the most suitable patch, and the size of the patch is also dynamically adjusted to make the misalignments within each patch controllable. Finally, considering the color inconsistency in the overlapping areas of neighboring images, an area-weighted image blending algorithm is also presented to achieve invisible seams and smooth transitions in the final mosaic. Not only does the proposed method produce mosaic images with minimal cloud coverage areas by excluding cloud pixels as much as possible, but it is also flexible for the mosaicking of images with varying degrees of misalignments, which is achieved by dynamically adjusting the size and position of each patch while maintaining texture consistency constraint. Both simulated experiments and real data experiments are carried out to verify the performance of the proposed method. The experimental results demonstrate that the proposed method can generate the mosaic image with higher spatial continuity and radiometric consistency.

中文翻译：

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基于动态变量斑块的灵活多时相正射影像镶嵌方法

正射影像镶嵌在环境监测和保护等遥感应用中发挥着重要作用。然而，遥感图像中的云覆盖往往会导致信息大量丢失和数据质量下降，给正射影像镶嵌带来诸多挑战。因此，本文提出一种基于动态变量补丁的灵活多时相正射影像镶嵌方法。与大多数现有的基于像素的镶嵌方法不同，该方法将块定义为正射影像镶嵌的最小处理单元，并且每个块的大小和位置是动态变化的。来自不同图像的补丁在图像纹理一致性约束下重新排列以生成马赛克图像。在该方法中，首先确定所有图像的可用斑块的初始位置，然后根据云覆盖率和图像的有效面积确定每个斑块的初始大小。随后，考虑到不同正射影像之间不可避免的错位，利用块之间的纹理相似性来选择最合适的块，并且动态调整块的大小以使每个块内的错位可控。最后，考虑到相邻图像重叠区域的颜色不一致，还提出了区域加权图像混合算法，以实现最终马赛克的隐形接缝和平滑过渡。该方法不仅通过尽可能排除云像素来生成云覆盖区域最小的马赛克图像，而且还可以通过动态调整云像素的大小和位置来灵活地对不同程度的未对准图像进行马赛克。每个补丁同时保持纹理一致性约束。进行了模拟实验和真实数据实验来验证所提方法的性能。实验结果表明，该方法能够生成具有较高空间连续性和辐射一致性的马赛克图像。