# A Segmentation-Based Optimal Seamline Generation Method for SAR Image Mosaic
###### Abstract  
In the mosaic creation of multiple high-resolution synthetic aperture radar (SAR) images, achieving an optimal seamline in overlapping areas is crucial for seamless and visually satisfactory results. Many existing seamline generation methods are designed primarily for optical remote sensing images, but due to the differing characteristics of SAR images and optical images, applying these methods directly to SAR images poses challenges in finding the optimal seamline. In response, this paper proposes a segmentation-based optimal seamline generation (SOSG) method for SAR image mosaics. The SOSG method involves a multi-step process. First, SAR image joint segmentation is performed within the overlapping areas. Subsequently, homogeneous areas are identified based on the segmentation results. Following this, a pixel cost matrix is constructed, incorporating homogeneous areas and intensity differences. Finally, the minimum path cost from the starting pixel to the end pixel is computed using the Dijkstra algorithm to determine the optimal path. To assess the feasibility and effectiveness of the proposed method, experiments are conducted using multiple SAR images from the Chinese Gaofen-3 01 satellite as datasets. The experimental results demonstrate that the proposed method yields seamless mosaic images when compared to other methods, while delivering satisfactory outcomes. This indicates the potential of the proposed method in addressing the unique challenges posed by SAR images and enhancing the quality of SAR image mosaics. s +
Footnote †: journal:limited. Addressing the diverse requirements of various research and applications has become progressively challenging due to these limitations. Consequently, the synthesis of a large-range SAR image is accomplished through the mosaicking of multiple SAR images. The mosaicking encompasses four key aspects [7]: SAR image registration, radiometric normalization, seamline generation, and image blending. SAR image registration is pivotal, ensuring consistent geometric alignment among multiple SAR images to be mosaicked. This alignment is fundamental for the success of the mosaicking process. Radiometric normalization plays a crucial role in minimizing radiometric inconsistencies between images within the SAR mosaic, ensuring visually satisfactory and coherent results. Seamline generation is an essential step in achieving a seamless mosaic and maintaining the integrity of ground objects. It involves determining the optimal location for the seamline among the images, considering factors such as geometry and radiometry. The generated seamlines serve as a basis for subsequent image blending. Image blending is the final step in the mosaicking process, aimed at eliminating slight radiometric differences near the seamlines. This enhances visual performance by creating a cohesive and aesthetically pleasing composite image. The comprehensive integration of these four aspects ensures the successful creation of large-range SAR mosaics that meet the diverse needs of various research and applications. In the realm of remote sensing image mosaicking, the generation of seamline stands out as a crucial step, prompting extensive exploration by scholars. The seamline generation for multiple images commonly involves an initial seamline network, subsequently refined for optimal results [8]. Various methods have been devised for the initial seamline network using Voronoi diagrams. [PERSON] et al. [9] employed a conventional Voronoi diagram based on a point set and images as the face set, but it led to blank space at the boundary. [PERSON] et al. [10] introduced a method using area Voronoi diagrams with overlap (AVDO), which proved efficient but showed limitations in handling complex polygons, especially concave ones. Another method proposed by [PERSON] et al. [11] utilized bounded Voronoi diagrams, employing geometric operations to crop diagrams for initial tessellations.