Underwater Image Stitching Method Based on AUV-guided Light Source Optimization

Ruonan Deng, Wei Qu, Chengjun Qiu, Jiuqiang Luo, Jiaqi Gao, Yuxuan Wu, Jiaqi Yan
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Abstract

Background: Image stitching is the procedure of combining two or more pictures having the same feature point location information into a panoramic image, which is useful in target discovery, seabed research, and military applications. Most of existing underwater picture stitching technology makes use of well-lit photos, however natural light gradually diminishes during propagation of underwater autonomous submersibles plunge further into the sea. When the image focuses on the regions of lighting concentration and the larger dark, image details are lost and feature points are not matched, the perspective transformation matrix obtained does not reflect the mapping relationship of the entire image, resulting in a poor stitching effect and making it difficult to meet practical application requirements. Objective: This study aims to obtain underwater images with a good enhancement effect and improve feature point matching image. Methods: An adaptive image enhancement method based on adaptive light source optimization is proposed in this paper, underwater photos are preprocessed to enhance images for the feature registration. Results: The experimental consequence indicate that the improvement algorithm can improve picture standard with better detail performance and color recovery by preprocessing submerged photographs. Conclusion: It is accomplished that high exactness for images stitching by adding the feature points of the enhanced image for feature alignment.
基于auv引导光源优化的水下图像拼接方法
背景:图像拼接是将具有相同特征点位置信息的两幅或多幅图像组合成全景图像的过程,在目标发现、海底研究和军事应用等方面都有广泛的应用。现有的大多数水下图像拼接技术都是利用光线充足的照片,然而在水下自主潜水器深入海洋的过程中,自然光线会逐渐减弱。当图像聚焦在光照集中区域和较大的黑暗区域时,图像细节丢失,特征点不匹配,得到的透视变换矩阵不能反映整个图像的映射关系,拼接效果较差,难以满足实际应用要求。目的:本研究旨在获得具有良好增强效果的水下图像,并对特征点匹配图像进行改进。方法:提出了一种基于自适应光源优化的自适应图像增强方法,对水下照片进行预处理,增强图像进行特征配准。结果:实验结果表明,改进算法可以提高图像标准,并通过对淹没照片进行预处理,获得更好的细节表现和色彩恢复。结论:通过添加增强图像的特征点进行特征对齐,实现了较高的图像拼接精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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