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Affine registration of multispectral images of historical documents for optimized feature recovery
Digital Scholarship in the Humanities ( IF 0.7 ) Pub Date : 2019-07-31 , DOI: 10.1093/llc/fqz054
Cerys Jones 1 , William A Christens-Barry 2 , Melissa Terras 3 , Michael B Toth 4 , Adam Gibson 1
Affiliation  

Abstract
Multispectral (MSI) imaging of historical documents can recover lost features, such as text or drawings. This technique involves capturing multiple images of a document illuminated using different wavelengths of light. The images created must be registered in order to ensure optimal results are produced from any subsequent image processing techniques. However, the images may be misaligned due to the presence of optical elements such as filters, or because they were acquired at different times or because the images were captured from different copies of the documents . There is little prior work or information available about which image registration techniques are most appropriate. Image registration of multispectral images is challenging as the illumination changes for each image and the features visible in images captured at different wavelengths may not appear consistently throughout the image sequence. Here, we compare three image registration techniques: two based on similarity measures and a method based on phase correlation. These methods are characterized by applying them to realistic surrogate images and then assessed on three different sets of real multispectral images. Mutual information is recommended as a measure for affine image registration when working with multispectral images of documentary material as it was proven to be more robust than the other techniques tested.


中文翻译:

仿射配准历史文档的多光谱图像以优化特征恢复

摘要
历史文档的多光谱(MSI)成像可以恢复丢失的特征,例如文本或图形。该技术涉及捕获使用不同波长的光照射的文档的多个图像。必须注册创建的图像,以确保从任何后续图像处理技术中都能获得最佳效果。然而,由于诸如滤光器的光学元件的存在,或者由于它们是在不同的时间获取的,或者因为图像是从文档的不同副本捕获的,所以图像可能未对准。关于哪种图像配准技术最合适的现有工作或信息很少。多光谱图像的图像配准具有挑战性,因为每个图像的照明度都会发生变化,并且在不同波长下捕获的图像中可见的特征可能不会在整个图像序列中始终出现。在这里,我们比较了三种图像配准技术:两种基于相似性度量的技术和一种基于相位相关性的方法。这些方法的特征是将它们应用于现实的替代图像,然后在三组不同的真实多光谱图像上进行评估。建议使用互信息来作为记录材料的多光谱图像处理时仿射图像配准的一种方法,因为事实证明,互信息比其他测试技术更可靠。两种基于相似性度量的方法和一种基于相位相关性的方法。这些方法的特征是将它们应用于现实的替代图像,然后在三组不同的真实多光谱图像上进行评估。建议使用互信息来作为记录材料的多光谱图像处理时仿射图像配准的一种方法,因为事实证明,互信息比其他测试技术更可靠。两种基于相似性度量的方法和一种基于相位相关性的方法。这些方法的特征是将它们应用于现实的替代图像,然后在三组不同的真实多光谱图像上进行评估。建议使用互信息来作为记录材料的多光谱图像处理时仿射图像配准的一种方法,因为事实证明,互信息比其他测试技术更可靠。
更新日期:2019-07-31
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