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Radiometric Calibration from Noise Distributions

Authors: Yasuyuki Matsushita; Stephen Lin 0001;

Radiometric Calibration from Noise Distributions

Abstract

A method is proposed for estimating radiometric response functions from noise observations. From the statistical properties of noise sources, the noise distribution for each scene radiance value is shown to be symmetric for a radiometrically calibrated camera. However, due to the non-linearity of camera response functions, the observed noise distributions become skewed in an uncalibrated camera. In this paper, we capitalize on these asymmetric profiles of measured noise distributions to estimate radiometric response functions. Unlike prior approaches, the proposed method is not sensitive to noise level, and is therefore particularly useful when the noise level is high. Also, the proposed method does not require registered input images taken with different exposures; only statistical noise distributions at multiple intensity levels are used. Real-world experiments demonstrate the effectiveness of the proposed approach in comparison to standard calibration techniques.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
48
Top 10%
Top 10%
Top 10%
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