Vector quantization and signal compression
Vector quantization and signal compression
Adaptive Dynamic Range Imaging: Optical Control of Pixel Exposures Over Space and Time
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Face detection for automatic exposure control in handheld camera
ICVS '06 Proceedings of the Fourth IEEE International Conference on Computer Vision Systems
Photoshop for Nature Photographers: A Workshop in a Book
Photoshop for Nature Photographers: A Workshop in a Book
Optimum auto exposure based on high-dynamic-range histogram
ISPRA'07 Proceedings of the 6th WSEAS International Conference on Signal Processing, Robotics and Automation
A new automatic exposure system for digital still cameras
IEEE Transactions on Consumer Electronics
Minimal-Bracketing Sets for High-Dynamic-Range Image Capture
IEEE Transactions on Image Processing
Automatic exposure correction of consumer photographs
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
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We introduce an algorithm to estimate the optimal exposure parameters from the analysis of a single, possibly under- or over-exposed, image. This algorithm relies on a new quantitative measure of exposure quality, based on the average rendering error, that is, the difference between the original irradiance and its reconstructed value after processing and quantization. In order to estimate the exposure quality in the presence of saturated pixels, we fit a log-normal distribution to the brightness data, computed from the unsaturated pixels. Experimental results are presented comparing the estimated vs. "ground truth" optimal exposure parameters under various illumination conditions.