Computational photography with novel camera sensors
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2016
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| Online Access: | http://hdl.handle.net/1721.1/103458 |
| _version_ | 1826192283518631936 |
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| author | Zhao, Hang, Ph.D. Massachusetts Institute of Technology |
| author2 | Ramesh Raskar. |
| author_facet | Ramesh Raskar. Zhao, Hang, Ph.D. Massachusetts Institute of Technology |
| author_sort | Zhao, Hang, Ph.D. Massachusetts Institute of Technology |
| collection | MIT |
| description | Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. |
| first_indexed | 2024-09-23T09:08:48Z |
| format | Thesis |
| id | mit-1721.1/103458 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T09:08:48Z |
| publishDate | 2016 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/1034582019-09-19T22:04:41Z Computational photography with novel camera sensors Zhao, Hang, Ph.D. Massachusetts Institute of Technology Ramesh Raskar. Massachusetts Institute of Technology. Department of Mechanical Engineering. Massachusetts Institute of Technology. Department of Mechanical Engineering Mechanical Engineering. Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2016. Cataloged from PDF version of thesis. Includes bibliographical references (pages 57-62). In this thesis, two computational camera designs are presented. They target two major goals in computational photography. high dynamic range (HDR) imaging and image superresolution (SR). HDR imaging refers to capturing both bright and dark details in the scenes simultaneously. A modulo camera does not get saturated during exposure, enabling HDR photography in a single shot without losing spatial resolutions. The second camera achieves image super-resolution with its non-conventional pixel design. It is shown that recording multiple images with a sensor of asymmetric sub-pixel layout increases the spatial sampling capability compared to a conventional sensor. Both proposed camera designs are the combination of novel imaging sensors and image recovering algorithms. Their potential applications include photography, robotics, and scientific research. Theoretical analyses and experiments are performed to validate our solutions. by Hang Zhao S.M. 2016-07-01T18:42:04Z 2016-07-01T18:42:04Z 2016 2016 Thesis http://hdl.handle.net/1721.1/103458 952180378 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 62 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Mechanical Engineering. Zhao, Hang, Ph.D. Massachusetts Institute of Technology Computational photography with novel camera sensors |
| title | Computational photography with novel camera sensors |
| title_full | Computational photography with novel camera sensors |
| title_fullStr | Computational photography with novel camera sensors |
| title_full_unstemmed | Computational photography with novel camera sensors |
| title_short | Computational photography with novel camera sensors |
| title_sort | computational photography with novel camera sensors |
| topic | Mechanical Engineering. |
| url | http://hdl.handle.net/1721.1/103458 |
| work_keys_str_mv | AT zhaohangphdmassachusettsinstituteoftechnology computationalphotographywithnovelcamerasensors |