The work of this thesis is motivated by the bene t of real-time HDR image processing which helps
constructing better seeing aid devices for day-to-day uses. The seeing aids with HDR can achieve
dynamic range greater than human eyes to capture visuals under various light conditions. Further, it
helps range sensing devices to read the light codes better. This requires realtime HDR image processing
running at 24 FPS. In this thesis, we demonstrate implementation of several HDR image compositing
and tone mapping methods in CUDA to achieve realtime performance. In addition, a new tone mapping
method termed PPEM is introduced as a novel tone mapping method by adjusting per pixel exposure.
Finally, we apply relevant HDR methods to range sensing devices for robust reading.
| Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/42868 |
| Date | 27 November 2013 |
| Creators | Huang, Shih-Chieh |
| Contributors | Mann, Steve |
| Source Sets | University of Toronto |
| Language | en_ca |
| Detected Language | English |
| Type | Thesis |
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