The course is going to:
- describe various approaches to achieve high dynamic range imaging
- predict the behavior of a given sensor or architecture on a scene
- specify the sensor or system requirements for a high dynamic range application
- classify a high dynamic range application into one of several standard types
The course notes are going to be published as a textbook.
Great course, i highly recommend!
ReplyDeleteA little expensive, given quite some material on HDR is available online and for free.
ReplyDeleteis there a lits of all the talked approaches?
ReplyDeletePART 1
ReplyDelete- Applications that require HDR
- HDR scenes
- HDR photography
PART 2
- Image sensor theory (noises, spectral response, FPN, SNR, CDS, etc)
- Definition of dynamic range
- Dynamic range gaps / SNR holes
- HVS
- Integrating linear pixels (rolling shutter and global shutter)
- Multi-segment pixels (several approaches)
- Multiple sampling pixels
- Multiple sensing nodes pixels
- Logarithmic pixels
- Logarithmic photovoltaic pixel
- Time to saturation pixel
- Gradient pixel
- Light to frequency pixel
- Prism methods
- Local methods
- Other methods
- XDR color imaging
PART 3
- Ideal software method
- Debevec
- Mann and Picard (brief)
- Mitsunaga and Nayar (brief)
- Robertson et al (brief)
- Tone mapping
- Special software method
PART 4
- Optical limitations
- Flare and ghosting
- Automatic HDR exposure
- Color spaces
- HDR file formats
- HDR testing
- Some demos