A Segmentation-Based Optimal Seamline Generation Method for SAR Image Mosaic

Author:

Liu Rui123ORCID,Zhu Jingxing123ORCID,Jiao Niangang12ORCID,Chen Yao12,You Hongjian123

Affiliation:

1. Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

2. Key Laboratory of Technology in Geo-Spatial Information Processing and Application Systems, Chinese Academy of Sciences, Beijing 100190, China

3. School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

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.

Funder

Future Star Foundation of Aerospace Information Research Institute, Chinese Academy of Sciences

Publisher

MDPI AG

Reference38 articles.

1. Detection of sand-covered geologic features in the Arabian Peninsula using SIR-C/X-SAR data;Dabbagh;Remote Sens. Environ.,1997

2. ALOS PALSAR: A pathfinder mission for global-scale monitoring of the environment;Rosenqvist;IEEE Trans. Geosci. Remote Sens.,2007

3. Yushu earthquake synergic analysis using multimodal SAR datasets;Guo;Chin. Sci. Bull.,2010

4. National sea area use dynamic monitoring based on GF-3 SAR imagery;Fan;J. Radars,2017

5. Mapping crop types in complex farming areas using SAR imagery with dynamic time warping;Gella;ISPRS J. Photogramm. Remote Sens.,2021

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