Abstract
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.
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Ilstrup, D., Manduchi, R. (2010). One-Shot Optimal Exposure Control. In: Daniilidis, K., Maragos, P., Paragios, N. (eds) Computer Vision – ECCV 2010. ECCV 2010. Lecture Notes in Computer Science, vol 6311. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15549-9_15
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DOI: https://doi.org/10.1007/978-3-642-15549-9_15
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