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Thesis

Machine learning in multi-frame image super-resolution

Abstract:

Multi-frame image super-resolution is a procedure which takes several noisy low-resolution images of the same scene, acquired under different conditions, and processes them together to synthesize one or more high-quality super-resolution images, with higher spatial frequency, and less noise and image blur than any of the original images. The inputs can take the form of medical images, surveillance footage, digital video, satellite terrain imagery, or images from many other sources...

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Institution:
University of Oxford
Research group:
Visual Geometry Group
Oxford college:
St Cross College
Department:
Mathematical,Physical & Life Sciences Division - Engineering Science
Role:
Author

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Role:
Supervisor
Role:
Supervisor
Publication date:
2007
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
Oxford University, UK
URN:
uuid:88c6968f-1e62-4d89-bd70-604bf1f41007
Local pid:
ora:12135

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