测绘学报2024,Vol.53Issue(8) :1598-1609.DOI:10.11947/j.AGCS.2024.20220690

基于L1范数混合主动轮廓的河流SAR图像分割

River SAR image segmentation using L1 norm based hybrid active con-tours

邢一波 韩斌 鲍秉坤
测绘学报2024,Vol.53Issue(8) :1598-1609.DOI:10.11947/j.AGCS.2024.20220690
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基于L1范数混合主动轮廓的河流SAR图像分割

River SAR image segmentation using L1 norm based hybrid active con-tours

邢一波 1韩斌 1鲍秉坤2
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作者信息

  • 1. 南京邮电大学通信与信息工程学院,江苏南京 210003
  • 2. 南京邮电大学计算机学院,江苏南京 210023
  • 折叠

摘要

为解决现有主动轮廓模型难以准确分割河流SAR图像的问题,提出一种基于L1范数的混合主动轮廓模型.首先,计算轮廓曲线内外区域像素灰度的中值作为区域拟合中心,以抑制SAR图像中干扰区域对其准确性的影响;然后,利用L1范数构建新的能量约束项并在模型能量泛函中引入边缘指示函数,进一步提升模型的分割性能;最后,将基于L1范数的中值和均值能量约束项结合起来并添加额外的区域拟合中心约束项,以提高模型的整体稳定性.针对实际河流SAR图像进行分割试验,结果表明,与现有分割方法相比,本文模型能更准确、稳定地分割河流SAR图像.

Abstract

To solve the problem that the existing active contour models are difficult to segment river SAR images accurately,this paper presents a hybrid active contour model based on the L1 norm.First,the median values of the pixel intensities in the inner and outer regions of the contour curve are calculated as the region fitting centers to suppress the influence of the interfer-ence regions in SAR images on their accuracies.Second,the L1 norm is used to construct a new energy constraint term and the edge indicator function is introduced into the model's energy functional to further enhance the segmentation performance.Final-ly,the median and mean energy constraint terms based on the L1 norm are combined and additional region-fitting center con-straint terms are added to improve the overall stability of the model.The segmentation experiments on real river SAR images show that the proposed model can segment river SAR images more accurately and stably than the existing models.

关键词

河流分割/SAR图像/主动轮廓模型/混合能量项/L1范数

Key words

river segmentation/SAR image/active contour model/hybrid energy term/L1 norm

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基金项目

国家自然科学基金(62325206)

国家自然科学基金(61936005)

国家自然科学基金(62201281)

江苏省自然科学基金(BK20220392)

南京邮电大学引进人才自然科学研究启动基金(NY222004)

出版年

2024
测绘学报
中国测绘学会

测绘学报

CSTPCDCSCD北大核心
影响因子:1.602
ISSN:1001-1595
被引量1
参考文献量26
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