Finite Sampling Corrected 3D Noise with Confidence Intervals软件

Analysis of imager noise through the use of 3D Noise model

软件应用简介

Analysis of imager noise through the use of 3D Noise model

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

% functions can be used
%    Example 1: Different calling methods
%    Example 2: Calculate Confidence Intervals from an UnBias Measurement
%    Example 3: Calculate Confidence Intervals from a Biased Measurement
%    Example 4: Conduct a Monte Carlo Simulation to look at distributions

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