通过内容感知曲和感知平衡来纠正和增强水下拼接图像
Laibin Chang1, Yunke Wang1, Bo Du1
1School of Computer Science, National Engineering Research Center for Multimedia Software, Institute of Artificial Intelligence, and Hubei Key Laboratory of Multimedia and Network Communication Engineering, Wuhan University, Wuhan, 430072, China.
概括
本研究介绍了UWIRE (Underwater Wide-field Image Rectangling and Enhancement) 框架,用于修复扭曲的水下图像. 使用单个输入图像,UWIRE有效地纠正不规则的边界,并提高视觉质量.
科学领域:
- 计算机视觉 计算机视觉
- 图像处理 图像处理
- 海洋技术 海洋技术
背景情况:
- 水下图像由于散射和吸收而受到有限的视野和糟糕的视觉感知.
- 现有的图像拼接方法产生不规则的边界,深度学习方法缺乏可靠的引用,导致扭曲.
研究的目的:
- 提出一个新的框架,UWIRE (水下广场图像矩形和增强),用于纠正和增强单个水下拼接图像.
- 为了解决视野,视觉感知和水下图像中边界扭曲的局限性.
主要方法:
- 该UWIRE框架包括一个R程序用于矩形不规则的边界使用形状调整和基于网格的扭曲与补充优化.
- 一个E-程序通过参数适应性校正和对颜色,对比度和纹理进行注意重量引导的融合来增强图像.
主要成果:
- 通过优化边界,结构和内容,R程序通过优化边界,结构和内容,以最小的扭曲来确保自然的外观.
- 电子程序平衡了跨道的信息分布,以提高图像质量.
- 综合实验表明,UWIRE在定量和定性评估中优于最先进的方法.
结论:
- 拟议的UWIRE框架有效地使用单个输入来纠正和增强水下拼接图像.
- 在不需要外部引用或复杂的设置的情况下,UWIRE提供了一个强大的解决方案来提高水下图像质量.
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