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Proceedings Paper

Acquiring and calibrating a high-dynamic-range natural image database
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Paper Abstract

Images recorded by digital cameras are invariably distorted by errors of CCD sensors and a series of camera operations in the imaging process. The distortion sources include noise, geometrical distortion, gamma correction, intensity and chromatic bias, blurring, etc. However, the true signal of the incident light needs to be known in many situations. In addition to traditional visual computing tasks such as shape from shading, color constancy, and photometric stereo, acquiring a large natural image database in which each image has a high-dynamic range and is carefully calibrated to reflect the true signal of the incident light is essential to human vision research. We recently acquired such a database containing 1600 images using an Olympus C2040 digital camera and explained a series of color perceptual phenomena based on the statistics of these images. We introduced in this paper the techniques we used for calibrating and acquiring this database, which include the methods to correct the spatial falloff, non-linearity, spectral bias, blurring, and noises and to obtain high-dynamic range for each image. The techniques presented here can be used in acquiring similar databases for a wide range of human vision and computer vision research fields.

Paper Details

Date Published: 17 January 2005
PDF: 7 pages
Proc. SPIE 5667, Color Imaging X: Processing, Hardcopy, and Applications, (17 January 2005); doi: 10.1117/12.588037
Show Author Affiliations
Fuhui Long, Duke Univ. (United States)
Hanchuan Peng, Lawrence Berkeley National Lab. (United States)

Published in SPIE Proceedings Vol. 5667:
Color Imaging X: Processing, Hardcopy, and Applications
Reiner Eschbach; Gabriel G. Marcu, Editor(s)

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