Synthetic Aperture Sonar Image Equalization Method Based on the Total Variation Retinex Framework

Heping ZHONG; Liang LEI; Han LI; Jinsong TANG

doi:10.12382/bgxb.2024.0615

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Synthetic Aperture Sonar Image Equalization Method Based on the Total Variation Retinex Framework

更新时间：2025-09-25

- Synthetic Aperture Sonar Image Equalization Method Based on the Total Variation Retinex Framework
- Acta Armamentarii Vol. 46, Issue 8, Pages: 240615(2025)
- 作者机构：
  
  海军工程大学, 湖北武汉 430033
- 作者简介：
- 基金信息：
- DOI：10.12382/bgxb.2024.0615
  CLC：
- Received：23 July 2024，
  
  Published Online：28 August 2025，
  
  Published：31 August 2025
- 稿件说明：
移动端阅览
Heping ZHONG, Liang LEI, Han LI, et al. Synthetic Aperture Sonar Image Equalization Method Based on the Total Variation Retinex Framework[J]. Acta Armamentarii, 2025, 46(8): 240615.
DOI：

Heping ZHONG, Liang LEI, Han LI, et al. Synthetic Aperture Sonar Image Equalization Method Based on the Total Variation Retinex Framework[J]. Acta Armamentarii, 2025, 46(8): 240615. DOI： 10.12382/bgxb.2024.0615.

摘要

针对合成孔径声纳图像灰度不均衡所带来的视觉分辨率低的问题

在结合声纳回波模型、斑点噪声统计特性、分解模型先验假设的基础上

提出一种基于全变分Retinex框架的合成孔径声纳图像均衡方法。根据图像中噪声瑞利乘性分布的特点和极大似然估计推导出考虑背景噪声的合成孔径声纳图像分解模型;针对地形、波束模式、沉积物角度响应和噪声影响

通过对照度分量的分段平滑约束

反射分量的沉积物回波强度信息约束和各向异性全变分约束

建立合成孔径声纳图像分解的目标函数。对照度分量增强后

与反射分量相乘得到均衡图像。实验结果表明

该模型解决了合成孔径声纳图像亮度不均衡的问题

极大地提升了亮度和对比度

在噪声抑制和图像均衡方面优于现有方法。

Abstract

To address the issue of low visual resolution caused by imbalanced grayscale in synthetic aperture sonar (SAS) images

a synthetic aperture sonar image equalization method based on the total variation framework is proposed by combining the sonar echo model

speckle noise statistical characteristics

and prior assumptions of decomposition model.The synthetic aperture sonar image decomposition model considering background noise is derived based on the Rayleigh distribution characteristics of multiplicative noise in the image and the maximum likelihood estimation.In response to the terrain and beam patterns of illumination component

the sediment angle response of reflection component

and the influence of noise

an objective function for the decomposition of synthetic aperture sonar images is established through the segmented smoothing constraints on the illumination component

the sediment echo intensity information constraints on the reflection component

and the anisotropic total variation constraints.Finally

after the contrast component is enhanced

a balanced image is obtained by multiplying it with the reflection component.The experimental results show that the proposed method solves the problem of uneven brightness of SAS images

greatly improves image brightness and contrast

and outperforms the methods in noise suppression and image equalization.

关键词

Keywords

references

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