计算机工程与应用 ›› 2024, Vol. 60 ›› Issue (18): 1-16.DOI: 10.3778/j.issn.1002-8331.2401-0161

• 热点与综述 • 上一篇    下一篇

太赫兹图像超分辨率重建方法的研究进展

蒋玉英,江梦蝶,葛宏义,张元,李广明,陈心雨,温茜茜,陈浩   

  1. 1.河南工业大学 粮食信息处理与控制教育部重点实验室,郑州 450001
    2.河南工业大学 河南省粮食光电探测与控制重点实验室,郑州 450001
    3.河南工业大学 人工智能与大数据学院,郑州 450001
    4.河南工业大学 信息科学与工程学院,郑州 450001
  • 出版日期:2024-09-15 发布日期:2024-09-13

Research and Progress on Super-Resolution Reconstruction Methods for Terahertz Images

JIANG Yuying, JIANG Mengdie, GE Hongyi, ZHANG Yuan, LI Guangming, CHEN Xinyu, WEN Xixi, CHEN Hao   

  1. 1.Key Laboratory of Grain Information Processing and Control, Ministry of Education, Henan University of Technology, Zhengzhou 450001, China
    2.Henan Provincial Key Laboratory of Grain Photoelectric Detection and Control, Henan University of Technology, Zhengzhou 450001, China
    3.School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou 450001,China
    4.School of Information Science and Engineering, Henan University of Technology, Zhengzhou 450001, China
  • Online:2024-09-15 Published:2024-09-13

摘要: 图像超分辨率是近几十年来图像处理领域的一个重要研究课题,旨在从低分辨率图像中重建出高分辨率图像,其突破了传感器和光学器件制造工艺和成本的限制,从算法方面提高图像分辨率,是一种简单、高效、低成本的方法。太赫兹(Terahertz,THz)图像受到THz波衍射和散射的影响,会产生图像模糊、纹理细节不清晰等问题,越来越多的学者致力于开发THz图像的超分辨率重建方法。根据近年来THz技术与超分辨率重建技术相关文献的研究,对THz图像的三大重建方法进行了详细阐述,重点对基于深度学习的方法进行介绍,并对比了各类算法的重建效果与优缺点;回顾了THz图像质量评价指标和常用数据集,并总结THz图像超分辨率重建技术的相关应用。最后,探讨了THz图像超分辨率重建技术的未来发展趋势。

关键词: 超分辨率重建, 太赫兹图像, 深度学习, 图像评价

Abstract: Image super resolution is an important research topic in image processing field in recent decades, aiming to reconstruct high resolution image from low resolution image. It breaks through the limitation of manufacturing process and cost of sensor and optical device, and improves image resolution from the aspect of algorithm, which is a simple, efficient and low-cost method. As an emerging technology, Terahertz (THz) technology has been widely used in many fields. Due to the influence of THz diffraction and scattering, THz images will produce image blur and unclear texture details. More and more scholars are committed to developing super-resolution reconstruction methods for THz images. Based on the research of the literature related to THz technology and super-resolution reconstruction technology in recent years, this paper elaborates the three major reconstruction methods of THz images, focuses on the introduction of deep learning-based methods, and compares the reconstruction effects, advantages and disadvantages of various algorithms. The THz image quality assessment indexes and the commonly used datasets are reviewed, and the super-resolution reconstruction technology of THz image related applications are summarized. Finally, the future development trend of THz image super-resolution reconstruction technology is discussed.

Key words: super-resolution reconstruction, Terahertz image, deep learning, image evaluation