Underwater multi-frame target images mosaic method based on adaptive image enhancement

基于自适应图像增强的水下多帧目标图像拼接融合方法

¹ School of Marine Science and Technology, Northwestern Polytechnical University, Xi’an 710072, China
² State Key Laboratory of Deep-Sea Manned Vehicles, China Ship Scientific Research Center, Wuxi 214082, China

Received: 8 December 2021

Abstract

The severe attenuation and scattering of light in the water reduces the effective field of view of the underwater camera, making the scene information contained in a single image limited, and it is difficult to meet the application requirements of the large-scale underwater scenes. To solve this problem, an underwater multi-frame target images mosaic method based on adaptive image enhancement is proposed in this paper. Firstly, the image blur prior is used to achieve the adaptive enhancement of underwater images to suppress the blur and colour distortion of underwater images. Then, the feature point matching method based on the improved SURF realizes the extraction and matching of the feature points of underwater multi-frame target images. Finally, combining with the fusion strategy of gradual in and out, the seamless splicing and fusion of underwater multi-frame target images is realized. The pool and shallow sea tests were carried out respectively, and the results show that the method proposed in this paper increases the number of effective feature point matching and improves the splicing effect.

摘要

光在水中的严重衰减和散射降低了水下相机的有效视场范围, 使得单幅图像所包含的场景信息有限, 难以满足水下大尺度场景的应用需求。针对该问题, 提出一种基于自适应图像增强的水下多帧目标图像拼接融合方法。利用图像模糊先验实现对水下图像的自适应增强, 抑制水下图像的模糊和颜色畸变; 基于改进SURF的特征点匹配方法实现了水下多帧目标图像特征点的提取与匹配; 结合渐入渐出的融合策略, 实现了水下多帧目标图像的无缝拼接融合。分别进行了水池和浅海试验, 结果表明所提方法在增加有效特征点匹配对数的同时提升了拼接的效果。