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

Xueyun Wei,Wei Zheng,Caiping Xi,Shang Shang

doi:10.3390/rs13040642

Xueyun Wei, Wei Zheng + Show 2 more

Open Access

https://doi.org/10.3390/rs13040642

Copy DOI

Journal: Remote Sensing	Publication Date: Feb 10, 2021
Citations: 19	License type: CC BY 4.0

Affiliation: Jiangsu University of Science and Technology

Abstract

Rapid and accurate extraction of shoreline is of great significance for the use and management of sea area. Remote sensing has a strong ability to obtain data and has obvious advantages in shoreline survey. Compared with visible-light remote sensing, synthetic aperture radar (SAR) has the characteristics of all-weather and all-day working. It has been well-applied in shoreline extraction. However, due to the influence of natural conditions there is a problem of weak boundary in extracting shoreline from SAR images. In addition, the complex micro topography near the shoreline makes it difficult for traditional visual interpretation and image edge detection methods based on edge information to obtain a continuous and complete shoreline in SAR images. In order to solve these problems, this paper proposes a method to detect the land–sea boundary based on a geometric active contour model. In this method, a new symbolic pressure function is used to improve the geometric active-contour model, and the global regional smooth information is used as the convergence condition of curve evolution. Then, the influence of different initial contours on the number and time of iterations is studied. The experimental results show that this method has the advantages of fewer iteration times, good stability and high accuracy.

Highlights

IntroductionThe main methods include boundary tracking algorithm, Markovian segmentation method, active contour model method, level set algorithm and so on
In order to solve the problem of weak boundary in synthetic aperture radar (SAR)-image shoreline extraction, this paper proposes a method of sea–land boundary detection based on a geometric activecontour model
The boundary tracking algorithm [9,10] first analyzes the normal distribution of ocean and land pixels in the image, and sets a threshold value according to the mean value and standard deviation to distinguish the ocean and land in the image to obtain the binary image

Summary

Introduction

The main methods include boundary tracking algorithm, Markovian segmentation method, active contour model method, level set algorithm and so on. The boundary-tracking algorithm is set to send out from a certain shoreline point to plot the boundary contour of ocean and land. Compared with the active-contour model, the geometric active conhas the advantages of natural handling of topological structure changes, insensitivity tour model has the advantages of natural handling of topological structure changes, into initial conditions and simple numerical implementation. These characteristics have sensitivity to initial conditions and simple numerical implementation. These characterisattracted more and more attention, and this model is widely used in computer vision and tics have attracted more and more attention, and this model is widely used in computer image processing.

Methods

Results

Discussion

Conclusion