Willard, Charles; (2022) Developments in Hyperspectral Imaging With Applications to Cultural Heritage. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Hyperspectral imaging is becoming widely adopted in the analysis of paintings and there is a trend towards capturing hyperspectral images at higher spatial resolutions. At higher spatial resolution, it is possible to identify more detail in an image (e.g. painting technique or pigment fragments) and better inform conservation treatment. There is a trade-off between hyperspectral imaging parameters such as spatial resolution, spectral quality and acquisition time, where an improvement in spatial resolution can be traded for improvements in other imaging parameters such as spectral quality. This work presents two methods towards the development of high-resolution hyperspectral imaging in chapter 3 and chapter 4. In chapter 3, style-transfer machine learning techniques are investigated to improve the spatial resolution of short-wave infrared sensors in conjunction with higher resolution image sensors such as a DSLR camera. A spectral imaging pipeline is proposed which uses style-transfer techniques, with reduced acquisition time compared to image mosaicking approaches. Chapter 4 investigates image mosaicking, combining multiple high-resolution hyperspectral images covering a narrow field-of-view. The images are acquired from a line-scan hyperspectral camera which can exhibit dropped frames, resulting in misalignments in the composite image. A method is developed to correct for dropped frames in high-resolution line-scan hyperspectral images. At high spatial resolution, three-dimensional aspects of a painting surface become more apparent. There are also numerous cultural artefacts which are threedimensional and would benefit from hyperspectral imaging, though methods to achieve this are not well established. One specific challenge comes from the spectral calibration process which often assumes a flat two-dimensional surface. The work in chapter 5 introduces a method to geometrically calibrate a line-scan hyperspectral camera with a video projector, enabling depth information to be extracted from the hyperspectral image via triangulation. A new method for spectral calibration in three spatial dimensions is also proposed.

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