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高动态范围图像生成方法研究进展

方明 刘宇轩

计算机科学与探索2026,Vol.20Issue(7):1861-1888,28.
计算机科学与探索2026,Vol.20Issue(7):1861-1888,28.DOI:10.3778/j.issn.1673-9418.2509013

高动态范围图像生成方法研究进展

Research Progress of High Dynamic Range Image Generation Methods

方明 1刘宇轩2

作者信息

  • 1. 长春理工大学 人工智能学院,长春 130022||长春理工大学 中山研究院,广东 中山 528403
  • 2. 长春理工大学 计算机科学技术学院,长春 130022
  • 折叠

摘要

Abstract

High dynamic range(HDR)images effectively represent the complex luminance distributions found in natural scenes,leading to significant advantages in highlights retention,shadow detail recovery,and overall visual fidelity.Conse-quently,HDR imaging has become a prominent research direction within the fields of computer vision and computational imaging.With the advancement of deep learning technologies and the growing demand for multi-scene perceptual applica-tions,HDR image generation techniques exhibit vast potential across various scenarios,including mobile photography,remote sensing imaging,intelligent surveillance,and industrial inspection.However,existing HDR image generation methods still face numerous challenges regarding imaging quality,detail reconstruction,generalization capabilities,and evaluation criteria.Furthermore,relevant research findings remain fragmented,lacking a systematic review and summary.To address this situation,this paper provides a comprehensive overview and analysis of the research progress in HDR image generation.Initially,based on different technical approaches to HDR image generation,existing methods are systematically categorized,highlighting the fundamental principles,development processes,applicable conditions,and their strengths and weaknesses.Next,commonly used performance evaluation metrics in HDR image generation tasks are compiled and analyzed,discussing the applicability and limitations of various metrics.Additionally,this paper summarizes the mainstream datasets frequently utilized in current HDR image generation research,examining their data sources,scale characteristics,scene coverage,and usage in training and testing,offering guidance for future research.Lastly,in conjunction with existing research findings and development trends,this paper anticipates potential future directions for HDR image generation technology.This paper aims to provide a systematic theoretical reference and method for HDR image generation-related research and to offer insights for subsequent algorithm design,dataset construction,and evalua-tion system enhancement.

关键词

高动态范围图像/色调映射/多曝光图像融合/深度学习

Key words

high dynamic range image/tone mapping/multi-exposure image fusion/deep learning

分类

信息技术与安全科学

引用本文复制引用

方明,刘宇轩..高动态范围图像生成方法研究进展[J].计算机科学与探索,2026,20(7):1861-1888,28.

基金项目

中山市科技局引进科研创新团队项目(CXTD2023005). This work was supported by the Scientific Research Innovation Team Project Introduced by Zhongshan Science and Technology Bureau(CXTD2023005). (CXTD2023005)

计算机科学与探索

1673-9418

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