Zaman Zainab, Ahmed Saad Bin, Malik Muhammad Imran
School of Electrical Engineering and Computer Science, National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan.
Department of Computer Science, Faculty of Science and Environmental Studies, Lakehead University, Thunder Bay, ON P7B 5E1, Canada.
Sensors (Basel). 2023 Aug 1;23(15):6845. doi: 10.3390/s23156845.
Hyperspectral data analysis is being utilized as an effective and compelling tool for image processing, providing unprecedented levels of information and insights for various applications. In this manuscript, we have compiled and presented a comprehensive overview of recent advances in hyperspectral data analysis that can provide assistance for the development of customized techniques for hyperspectral document images. We review the fundamental concepts of hyperspectral imaging, discuss various techniques for data acquisition, and examine state-of-the-art approaches to the preprocessing, feature extraction, and classification of hyperspectral data by taking into consideration the complexities of document images. We also explore the possibility of utilizing hyperspectral imaging for addressing critical challenges in document analysis, including document forgery, ink age estimation, and text extraction from degraded or damaged documents. Finally, we discuss the current limitations of hyperspectral imaging and identify future research directions in this rapidly evolving field. Our review provides a valuable resource for researchers and practitioners working on document image processing and highlights the potential of hyperspectral imaging for addressing complex challenges in this domain.
高光谱数据分析正被用作一种有效且有说服力的图像处理工具,为各种应用提供前所未有的信息和见解。在本手稿中,我们汇编并全面概述了高光谱数据分析的最新进展,可为开发针对高光谱文档图像的定制技术提供帮助。我们回顾了高光谱成像的基本概念,讨论了各种数据采集技术,并考虑文档图像的复杂性,研究了高光谱数据预处理、特征提取和分类的最新方法。我们还探讨了利用高光谱成像应对文档分析中的关键挑战的可能性,包括文档伪造、墨水年代估计以及从退化或受损文档中提取文本。最后,我们讨论了高光谱成像当前的局限性,并确定了这个快速发展领域未来的研究方向。我们的综述为从事文档图像处理的研究人员和从业人员提供了宝贵的资源,并突出了高光谱成像在解决该领域复杂挑战方面的潜力。