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Volume: 22 | Article ID: art00047
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Image Sensor Modeling: Color Measurement at Low Light Levels
  DOI :  10.2352/CIC.2014.22.1.art00047  Published OnlineNovember 2014
Abstract

The investigation of low light imaging is of high importance in the field of color science from different perspectives. One of the most important challenges that arises at low light levels is the issue of noise or, more generally speaking, low signal-to-noise ratio (SNR). In the present work, effects of different image sensor noises, such as photon noise, dark current noise, read noise, and quantization error are investigated in low light color measurements. In this regard, a typical image sensor is modeled and employed for this study. A detailed model of noise is considered in the process of implementing the image sensor model to guarantee the precision of the results. Several experiments have been performed over the implemented framework and the results show the following: first, photon noise, read noise, and quantization error lead to uncertain measurements distributed around the noise free measurements and these noisy samples form an elliptical shape in the chromaticity diagram; second, even for an ideal image sensor, in very dark situations, stable measurement of color is impossible due to the physical limitation imposed by the fluctuations in photon emission rate; third, dark current noise reveals dynamic effects on color measurements by shifting their chromaticities towards the chromaticity of the camera black point; fourth, dark current dominates the other sensor noise types in the image sensor in terms of affecting measurements. Moreover, an SNR sensitivity analysis against the noise parameters is presented over different light intensities. © 2014 Society for Imaging Science and Technology. [DOI:10.2352/J.ImagingSci.Technol.2014.58.3.030401]

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Mehdi Rezagholizadeh, James J. Clark, "Image Sensor Modeling: Color Measurement at Low Light Levelsin Proc. IS&T 22nd Color and Imaging Conf.,  2014,  pp 265 - 275,  https://doi.org/10.2352/CIC.2014.22.1.art00047

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Copyright © Society for Imaging Science and Technology 2014
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