Willard, Charlie;
Wade, Nancy;
Strlič, Matija;
Gilchrist, John R;
Weyrich, Tim;
Gibson, Adam;
(2022)
Correction of Dropped Frames in High-resolution Push-broom Hyperspectral Images for Cultural Heritage.
Journal on Computing and Cultural Heritage
, 15
(2)
, Article 29. 10.1145/3479011.
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Abstract
Dropped frames can occur in line-scan cameras, which result in non-uniform spatial sampling of the scene. A dropped frame occurs when data from an image sensor is not successfully recorded. When mosaicking multiple line-scan images, such as in high-resolution imaging, this can cause misalignment. Much previous work to identify dropped frames in video prioritises fast computation over high accuracy, whereas in heritage imaging, high accuracy is often preferred over short computation time. Two approaches to identify the position of dropped frames are presented, both using the A* search algorithm to correct dropped frames. One method aligns overlapping sections of push-broom images and the other aligns the push-broom image to a lower resolution reference image. The two methods are compared across a range of test images, and the method aligning overlapping sections is shown to perform better than the method using a reference image under most circumstances. The overlap method was applied to hyperspectral images acquired of La Ghirlandata, an 1873 oil on canvas painting by D. G. Rossetti, enabling a high-resolution hyperspectral image mosaic to be produced. The resulting composite image is 10,875 \( \times \) 14,697 pixels each with 500 spectral bands from 400–2,500 nm. This corresponds to a spatial resolution of \( 80 \,\mathrm{\upmu }\mathrm{m} \) and a spectral resolution of 3–6 nm.
| Type: | Article |
|---|---|
| Title: | Correction of Dropped Frames in High-resolution Push-broom Hyperspectral Images for Cultural Heritage |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/3479011 |
| Publisher version: | https://doi.org/10.1145/3479011 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of the Built Environment > Bartlett School Env, Energy and Resources UCL > Provost and Vice Provost Offices > UCL BEAMS UCL UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10147459 |
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