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

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

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

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9 The Problem of Dynamic Range Dynamic Range: Range of brightness values measurable with a camera (Hood 1986) 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!! Today’s Cameras: Limited Dynamic Range

10 Images taken with a fish-eye lens of the sky show the wide range of brightnesses. 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). (Debevec) (Mitsunaga)

11 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. Irradiance = const * Reflectance Pixel Values 3.1%9.0%19.8%36.2%59.1%90% 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. 0 255 01 g ? ?

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