Kalman filter for noisy movies
Run exampleFilter.m to see how the algorithm performs on a sample of moderately noisy 2-photon imaging data. This function is a faster, vectorised, version of Java code written by C.P. Mauer as part of an ImageJ plugin (see below).
function imageStack=Kalman_Stack_Filter(imageStack,percentvar,gain)
Purpose
Implements a predictive Kalman-like filter in the time domain of the image stack. Algorithm taken from Java code by C.P. Mauer. http://rsb.info.nih.gov/ij/plugins/kalman.html
Inputs
imageStack - a 3d matrix comprising of a noisy image sequence. Time is
the 3rd dimension.
gain - the strength of the filter [0 to 1]. Larger gain values means more
aggressive filtering in time so a smoother function with a lower
peak. Gain values above 0.5 will weight the predicted value of the
pixel higher than the observed value.
percentvar - the initial estimate for the noise [0 to 1]. Doesn't have
much of an effect on the algorithm.
Output
imageStack - the filtered image stack
Note:
The time series will look noisy at first then become smoother as the
filter accumulates evidence.
Rob Campbell, August 2009
引用格式
Rob Campbell (2024). Kalman filter for noisy movies (https://www.mathworks.com/matlabcentral/fileexchange/26334-kalman-filter-for-noisy-movies), MATLAB Central File Exchange. 检索来源 .
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