Finite Sampling Corrected 3D Noise with Confidence Intervals
The 3D noise model is a white noise approximation consisting of 7 independent contributions that span the 3D correlation space (1 one dimensional uncorrelated processes, 3 two dimensional uncorrelated processes, and one three dimensional uncorrelated process). These scripts allow the user to simulate a noise cube, calculate the 7 independent variances, and calculate the confidence intervals. An additional script provides examples of how the functions can be called under different circumstances, for example correcting a past measurement, or iteratively calculating the noise cube by chunking the data.
This code is in support of a journal article "Finite Sampling Corrected 3D Noise with Confidence Intervals" https://www.osapublishing.org/ao/abstract.cfm?uri=ao-54-15-4907
Citation pour cette source
David Haefner (2024). Finite Sampling Corrected 3D Noise with Confidence Intervals (https://www.mathworks.com/matlabcentral/fileexchange/49657-finite-sampling-corrected-3d-noise-with-confidence-intervals), MATLAB Central File Exchange. Récupéré le .
Compatibilité avec les versions de MATLAB
Plateformes compatibles
Windows macOS LinuxCatégories
- Image Processing and Computer Vision > Image Processing Toolbox > Geometric Transformation and Image Registration >
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Remerciements
A inspiré : Noise3d_Spatial, IR Noise Evaluation
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Noise3d
Version | Publié le | Notes de version | |
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1.3.0.0 | Added support for trend removal, see IR noise evaluation for examples |
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1.2.0.0 | Corrected file organization in zip file |
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1.1.0.0 | % 05-19-2015 DH; Modified 0 defective case to allow large V and H input
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1.0.0.0 |