极度度图像恢复方法与域对抗学习用于水下成像
Fei Tian1, Jiuming Xue2, Zhedong Shi2
1School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
Scientific reports
|January 31, 2025
概括
本研究介绍了UPD-Net,这是一个用于水下图像恢复的新型神经网络. 它通过使用域对抗学习有效地恢复各种水条件的退化图像.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 光学是什么?光学是什么?光学是什么?
背景情况:
- 水下图像由于散射和吸收而遭受退化 (颜色变化,低对比度).
- 现有的方法在各种水类的域泛化方面扎.
- 极化信息对于改善水下图像质量至关重要.
研究的目的:
- 开发一种强大的方法来恢复退化的水下彩色图像.
- 为了应对水下图像修复中域概括的挑战.
- 为了利用偏振信息进行增强的图像恢复.
主要方法:
- 收集了最丰富的极化色彩图像数据集,跨越不同水类.
- 提出了UPD-Net,一个采用域对抗学习的神经网络.
- 集成了水类型分类器和生成对抗式学习,用于图像恢复.
主要成果:
- 在视觉效果和定量指标方面取得了最先进的性能.
- 在可见和不可见的水下环境中表现出强大的恢复能力,包括水.
- 成功恢复了清晰的彩色图像和线性极化度 (DoLP) 图像.
结论:
- 拟议的UPD-Net有效地恢复了各种水条件下的退化水下图像.
- 域对抗性学习使得水下图像恢复的强大概括成为可能.
- 该方法显示了对现实世界水下成像和识别应用的巨大潜力.
相关概念视频
01:11Buoyancy and Stability for Submerged and Floating Bodies
In fluid mechanics, buoyancy and stability are key concepts for understanding the behavior of submerged and floating bodies. When a stationary body is fully or partially submerged in a fluid, the fluid exerts a force on the body known as the buoyant force. This force acts vertically upward through a point called the center of buoyancy, which is the center of the displaced fluid volume. According to Archimedes' principle, the magnitude of the buoyant force is equal to the weight of the fluid...
01:18Uniform Depth Channel Flow: Problem Solving
To calculate the flow rate for a trapezoidal channel, first, identify the bottom width, side slope, and flow depth of the channel. The cross-sectional area (A) corresponding to the depth of flow (y), channel bottom width (B), and side slope (θ) is determined by:Next, calculate the wetted perimeter, which includes the bottom width and the sloped side lengths in contact with the water. Using the values of the cross-sectional area and the wetted perimeter, determine the hydraulic radius by...