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Volume: 32 | Article ID: art00028
Noise Power Spectrum Scene-Dependency in Simulated Image Capture Systems
  DOI :  10.2352/ISSN.2470-1173.2020.9.IQSP-345  Published OnlineJanuary 2020

The Noise Power Spectrum (NPS) is a standard measure for image capture system noise. It is derived traditionally from captured uniform luminance patches that are unrepresentative of pictorial scene signals. Many contemporary capture systems apply nonlinear content-aware signal processing, which renders their noise scene-dependent. For scene-dependent systems, measuring the NPS with respect to uniform patch signals fails to characterize with accuracy: i) system noise concerning a given input scene, ii) the average system noise power in real-world applications. The sceneand- process-dependent NPS (SPD-NPS) framework addresses these limitations by measuring temporally varying system noise with respect to any given input signal. In this paper, we examine the scene-dependency of simulated camera pipelines in-depth by deriving SPD-NPSs from fifty test scenes. The pipelines apply either linear or non-linear denoising and sharpening, tuned to optimize output image quality at various opacity levels and exposures. Further, we present the integrated area under the mean of SPD-NPS curves over a representative scene set as an objective system noise metric, and their relative standard deviation area (RSDA) as a metric for system noise scene-dependency. We close by discussing how these metrics can also be computed using scene-and-processdependent Modulation Transfer Functions (SPD-MTF).

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Edward W. S. Fry, Sophie Triantaphillidou, Robin B. Jenkin, Ralph E. Jacobson, John R. Jarvis, "Noise Power Spectrum Scene-Dependency in Simulated Image Capture Systemsin Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Quality and System Performance XVII,  2020,  pp 345-1 - 345-7,

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