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16421: Vision Sensors

16421: Vision Sensors. Lecture 7: High Dynamic Range Imaging Instructor: S. Narasimhan Wean 5312, T-R 1:30pm – 3:00pm. Paul Debevec’s SIGGRAPH Course. The Problem of Dynamic Range. Dynamic Range: Range of brightness values measurable with a camera. (Hood 1986).

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16421: Vision Sensors

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  1. 16421: Vision Sensors Lecture 7: High Dynamic Range Imaging Instructor: S. Narasimhan Wean 5312, T-R 1:30pm – 3:00pm

  2. Paul Debevec’s SIGGRAPH Course

  3. The Problem of Dynamic Range • Dynamic Range: Range of brightness values measurable with a camera (Hood 1986) • Today’s Cameras: Limited Dynamic Range High Exposure Image Low Exposure Image • We need about 5-10 million values to store all brightnesses around us. • But, typical 8-bit cameras provide only 256 values!!

  4. High Dynamic Range Imaging • Capture a lot of images with different exposure settings. • Apply radiometric calibration to each camera. • Combine the calibrated images (for example, using averaging weighted by exposures). (Mitsunaga) (Debevec) Images taken with a fish-eye lens of the sky show the wide range of brightnesses.

  5. Radiometric Calibration – RECAP • Important preprocessing step for many vision and graphics algorithms such as • photometric stereo, invariants, de-weathering, inverse rendering, image based rendering, etc. • Use a color chart with precisely known reflectances. 255 ? Pixel Values g 0 ? 0 1 90% 59.1% 36.2% 19.8% 9.0% 3.1% Irradiance = const * Reflectance • Use more camera exposures to fill up the curve. • Method assumes constant lighting on all patches and works best when source is • far away (example sunlight). • Unique inverse exists because g is monotonic and smooth for all cameras.

  6. [Greg Ward]

  7. [Greg Ward] [Greg Ward]

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