基于区域优化的图像拼接技术研究及应用进展

Progress in Research and Application of Image Stitching Technology Based on Regional Optimization

光电成像技术作为获取环境信息和感知物理世界的重要手段,在航空遥感观测、农业资源监测、工业缺陷检测、生物医学诊断等领域具有愈发广泛的应用。随着应用场景不断拓展,光电成像技术常常面临大视场和高分辨率难以兼顾的问题,为此必须开发精准高效的图像拼接技术。在阐明图像拼接理论模型的基础上,分类介绍了基于区域优化的图像拼接技术的基本原理和实现方法,并从方法特点、拼接效果、时间效率等角度,分析了现有基于区域优化的图像拼接方法的优越性和局限性。通过阐述图像拼接技术在典型领域的应用,总结了图像拼接所面临的技术挑战和应用前景,并展望了其在适应复杂应用场景、融合深度学习方法、提升信息维度等方面的发展方向。

Optoelectronic imaging technology is crucial for obtaining environmental information and perceiving the physical world.This technology is widely used in diverse fields,such as aerial remote sensing observation,agricultural resource monitoring,industrial defect detection,and biomedical diagnosis.With the continuous expansion of application scenarios,optoelectronic imaging technology often faces the challenge of balancing a large field of view with high resolution.Therefore,developing accurate and efficient image stitching technology is necessary.This study elucidates the theoretical model of image stitching and classifies and introduces the basic principles and implementation methods of image stitching technology based on regional optimization.This study also analyzes the advantages and limitations of existing regional optimization-based image stitching methods in terms of method characteristics,stitching effect,and time efficiency.By elucidating the application of image stitching technology in typical fields,this paper summarizes the technical challenges and application prospects of image stitching and explores its development in adapting to complex application scenarios,integrating deep learning methods,and improving information dimensions.