Accurate sea–land segmentation using ratio of average constrained graph cut for polarimetric synthetic aperture radar data

Abstract

Xiaoqiang She, Xiaolan Qiu, Bin Lei, "Accurate sea-land segmentation using ratio of average constrained graph cut for polarimetric synthetic aperture radar data," J. Appl. Remote Sens. 11(2), 026023 (2017), doi: 10.1117/1.JRS.11.026023. Abstract. Separating sea surface and land areas in synthetic aperture radar (SAR) images is challenging yet of great importance to coastline extraction and subsequent coastal classification.Results of the previous state-of-art methods often suffer from a number of limitations that arise from the presence of the speckle effect and the inadequate returned signal around the boundaries. We propose a graph cut (GC)-based approach to tackle these limitations and achieve accurate sea-land segmentation results. To be more specific, as the first step, three powerful multipolarization features are extracted from the polarimetric SAR data as descriptors to fully characterize the sea area and land area. Starting from that, seeds of the sea and land are selected automatically to build the prior model for GC. Based on the prior model, we construct the undirected graph in GC using the multipolarization descriptors. Finally, we incorporate the ratio of average operator to eliminate the speckle effect and get finer results for some finer structures. Experiments on Radarsat-2 quad-polarization images demonstrate significantly improved results of our proposed algorithms compared with several state-of-the-art methods in terms of both quantitative and visual performance.

A Quality Assessment Method Based on Common Distributed Targets for GF-3 Polarimetric SAR Data

“…PolSAR can obtain multidimensional data that describe polarization scattering information of targets. And it has many important applications in target classification [ 1 , 2 ], target detection [ 3 , 4 ], biomass inversion [ 5 , 6 ] and so on. Many countries have paid attention to the development of PolSAR systems, and have launched a series of space-borne PolSAR systems, such as Radarsat-2, TerraSAR-X, ALOS-2, Sentinel-1 and Cosmo-Skymed.…”

Shoreline Extraction in SAR Image Based on Advanced Geometric Active Contour Model

“…Finally, the shoreline is obtained. However, the method of Markovian random field and simulated annealing still has errors in the classification of pixels in the image, and the amount of calculation is relatively large [14].…”

“…Shoreline extraction methods based on multipolarization SAR have also been proposed [14,23]. In [23], radar frequency was shown to have great influence on the method of SAR-based shoreline extraction.…”

Current Trends and Future Directions in Sea-Land Segmentation for Remote Sensing Images

“…She et al [37] developed a new method based on graph cut (GC) to solve the sea-land segmentation problems for PolSAR images. The multi-polarization features were utilized for automatic seed selection for the sea and land to build a graph model for GC.…”

“…There are other factors that may cause strong scattering in the sea regions and lead to nonhomogeneous characteristics of the sea surface coarseness such as wave, wind, clouds, and sea ice. Also, the lack of color information, the land regions are complex, and the poor discrimination of sea-land areas may produce discontinuous boundaries [37].  Infrared RSIs usually suffer from main issues including low contrast ratios, complex scene information, and bipolar problem.…”