A Technique for Evaluation of CCD Video-Camera Noise

Irie, Kenji; McKinnon, Alan E.; Unsworth, K.; Woodhead, Ian

doi:10.1109/tcsvt.2007.913972

Cited by 64 publications

(35 citation statements)

References 6 publications

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“…Farrell et al described a noise model that includes readout noise, dark-current, offset FPN, PRNU, and photon shot noise [17]. Irie and co-workers presented a comprehensive measurement of CCD digital-video camera noise based on the physical characteristics in the acquisition and sampling of photons through the image capture process [18,19]. The model incorporates all noise sources, including PRNU, photon shot noise SN ph , offset FPN, dark-current shot noise SN dark , readout noise N read , demosaicing noise N D , digital filtering noise N filt , as well as quantization noise N Q .…”

Section: Ccd Camera Noise Modelmentioning

confidence: 99%

Impact of CCD camera SNR on polarimetric accuracy

et al. 2014

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A comprehensive charge-coupled device (CCD) camera noise model is employed to study the impact of CCD camera signal-to-noise ratio (SNR) on polarimetric accuracy. The study shows that the standard deviations of the measured degree of linear polarization (DoLP) and angle of linear polarization (AoLP) are mainly dependent on the camera SNR. With increase in the camera SNR, both the measurement errors and the standard deviations caused by the CCD camera noise decrease. When the DoLP of the incident light is smaller than 0.1, the camera SNR should be at least 75 to achieve a measurement error of less than 0.01. When the input DoLP is larger than 0.5, a SNR of 15 is sufficient to achieve the same measurement accuracy. An experiment is carried out to verify the simulation results.

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Section: Ccd Camera Noise Modelmentioning

confidence: 99%

Impact of CCD camera SNR on polarimetric accuracy

et al. 2014

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“…For the addressed simulation, two major effects will be considered: light bleeding and image noise. The following equation is suitable for a generic sensor noise simulation [150]: I n (x, y) = I(x, y) + r( f sn (I(x, y))), (5.3) where I n is the image including noise, I stands for the input image, f sn for a signal to noise ratio function and r(i) for a random number generator. Crosstalk describes the effect that a pixel sensor spreads the received energy to adjacent ones if the energy difference between both sensors lies above a certain limit.…”

Section: Sensor Featuresmentioning

confidence: 99%

Bridging the Gap between Rendering and Simulation Frameworks

Hempe

2016

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the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.Printed on acid-free paper This Springer Vieweg imprint is published by Springer Nature The registered company is Springer Fachmedien Wiesbaden GmbH Dissertation RWTH Aachen, 2015 D 82 ForewordAfter nearly half a century of research, the Holy Grail of the field of computer graphics remains a comprehensive computational model and the corresponding software structure to provide realistically looking -and behaving -virtual world. However, Nico Hempe's work, documented in this thesis achieves nothing less than a functional and proven software structure to cope with the request for realism in the ever increasing complexity of today's robotic and mechatronic applications. Over the decades, modeling for computer simulation and visualization has progressed from an early reliance on purely geometric models to extremely powerful simulation models which also incorporate the underlying physical principles. Nico's is to date one of the most important PhD dissertations which manage to bridge the gap between advanced simulation and comprehensive rendering techniques by combining the best of both worlds to impressive virtual reality applications. His virtual worlds, which do not only look good but serve as the basis for virtual testbeds, are key components in new development approaches in the context of eRobotics and "Industry 4.0". Starting in 2010, Nico's work helped to establish the research field of eRobotics in order to cope with the inherent complexity, facilitate the development and significantly cut down the cost of advanced robotics and mechatronics applications. The objective is to effectively use electronic media -hence the "e" at the beginning of the term -to achieve the best possible advancements in the development of the robots' respective fields of use. Current domains of eRobotics covered by Nico's work comprise industrial robotics, work machines, construction site automation, space robotics and even the fields of environmental and city modelling. This thesis reveals the technical details behind a spectacular accomplishment in com...

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“…This can potentially be the basis for a discussion of practical significance versus statistical significance. For a discussion of the various sources of color channel noise, the interested reader is directed to Irie et al (2008).…”

Section: Hypothesis Testingmentioning

confidence: 99%

Teaching the assessment of normality using large easily‐generated real data sets

Kulp

Sprechini

2016

Teaching Statistics

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Summary A classroom activity is presented, which can be used in teaching students statistics with an easily generated, large, real world data set. The activity consists of analyzing a video recording of an object. The colour data of the recorded object can then be used as a data set to explore variation in the data using graphs including histograms, quantile–quantile plots and scatterplots, and to indicate possible formal analyses.

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A Technique for Evaluation of CCD Video-Camera Noise

Cited by 64 publications

References 6 publications

Impact of CCD camera SNR on polarimetric accuracy

Impact of CCD camera SNR on polarimetric accuracy

Bridging the Gap between Rendering and Simulation Frameworks

Teaching the assessment of normality using large easily‐generated real data sets

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