水下图像视野增强研究综述
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作者单位:

北京科技大学 自动化学院,北京 100083

作者简介:

庄培显(1988-),男,博士,副教授,主要从事海洋信息观测和水下视觉处理研究。

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中图分类号:

TN911.73

基金项目:

国家自然科学基金面上项目“基于先验知识与数据驱动景深估计模型的神经元提取研究”(62171252);国家自然科学基金青年科学基金项目“基于非参数层次贝叶斯景深估计模型的水下降质图像质量提升研究”(61701245)


Review of Underwater Image Field-of-View Enhancement Research
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Affiliation:

School of Automation,University of Science and Technology Beijing,Beijing 100083 ,China

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    摘要:

    为解决传统水下成像视野受限、信息缺失等问题,拓展真实水下环境有效视觉范围,为后续研究提供新视角及发展方向,采用综述研究法,依据技术实现路径将水下图像视野增强分为水下鱼眼图像畸变校正和水下图像拼接 2 类,从方法论与系统架构角度对 2 类技术的原理、系统构成及现有成果进行系统梳理与深入分析。研究明确了 2 类技术核心内容与系统架构,剖析现有成果,优化图像空间延展与细节还原,弥补传统水下成像不足,同时探讨当前技术发展关键挑战。综上,水下图像视野增强技术作为融合图像处理算法与水下场景特性的新兴技术,缓解传统水下成像视野受限问题,并具有显著应用价值。此外,还探讨了水下图像视野增强面临的关键挑战,并对其未来发展的潜在方向进行探索。

    Abstract:

    To solve the problems of limited field of view and information deficiency in traditional underwater imaging,and to expand the effective visual range of the real underwater environment to provide a new perspective for subsequent research and to explore the development direction of technology,a review research method is adopted in this paper. Based on the technical implementation path,the underwater image field-of-view(FOV)enhancement is divided into two categories:underwater fisheye image correction and underwater image stitching. A systematic review and in-depth analysis of the principles,system composition and existing achievements of the two types of technologies are conducted from the perspectives of methodology and system architecture. The core contents and system architectures of the two types of technologies are clarified. The existing achievements are analyzed. Then,the image space extension and detail restoration are optimized to make up for the shortcomings of traditional underwater imaging. At the same time,the key challenges in current technological development are discussed. In summary, underwater image FOV enhancement technology,as an emerging technology that integrates image processing algorithms and underwater scene characteristics,can alleviate the problem of traditional underwater imaging FOV limitation,has significant application value. In addition,the key challenges of underwater image FOV are discussed and the potential directions for its future development are explored.

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庄培显,刘飞,童俊杰,等. 水下图像视野增强研究综述[J]. 数字海洋与水下攻防,2025,8(4):390-400.

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  • 收稿日期:2025-07-26
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  • 在线发布日期: 2025-09-29
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