对复杂物体的基于自适应分区的水下极化图像恢复方法
Shenghui Zhang1, Ronghua Li2,3, Yuanyi Fan1
1School of Mechanical Engineering, Dalian Jiaotong University, Dalian, 116028, China.
Scientific reports
|November 18, 2025
概括
这项研究引入了一种适应性水下极化成像方法,可以对复杂的目标进行细分. 这种方法通过分析不同区域的极化特征来提高图像重建质量.
科学领域:
- 光学工程是指光学工程.
- 图像处理 图像处理
- 遥感 遥感 遥感 遥感
背景情况:
- 水下成像依赖于偏振信息,但目标具有复杂的,可变的偏振特征.
- 现有的方法难以处理包含高极化和低极化目标或单一目标中的区域的场景.
研究的目的:
- 为复杂物体开发一种基于分区的适应性水下极化成像方法.
- 为了提高复杂的极化特性对象的图像重建质量.
主要方法:
- 使用图像贡献运算符 (区域大小和错误控制运算符) 的适应分区策略.
- 对每个分区区域的偏振特征的个别估计.
- 复杂目标的水下极化成像的应用.
主要成果:
- 该方法根据极化特征对目标图像进行自适应分区.
- 在各种水下场景中成功地改善了复杂目标的图像恢复.
- 在不同水度的水中表现出强度.
结论:
- 拟议的自适应分区方法有效地处理水下成像中的复杂偏振特征.
- 与用于具有挑战性的目标的传统方法相比,实现更优质的图像重建质量.
- 在各种环境条件下为水下目标成像提供强大的解决方案.
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