Correct images for bleaching (or any other effect that introduces an unwanted trend) by detrending.
img_detrend_robinhood(img, swaps = "auto", quick = FALSE) img_detrend_rh(img, swaps = "auto", quick = FALSE) img_detrend_boxcar(img, l, purpose = c("FCS", "FFS"), parallel = FALSE) img_detrend_exp( img, tau, cutoff = 0.05, purpose = c("FCS", "FFS"), parallel = FALSE ) img_detrend_polynom(img, degree, purpose = c("FCS", "FFS"), parallel = FALSE)
img  A 4dimensional array in the style of an
ijtiff_img (indexed by 

swaps  The number of swaps (giving of one count from rich to poor) to
perform during the Robin Hood detrending. Set this to "auto" (the
default) to use Nolan's algorithm to automatically find a suitable value
for this parameter (recommended). For multichannel images, it is possible
to have a different 
quick  If 
l  The length parameter for boxcar detrending. The size of the
sliding window will be 
purpose  What type of calculation do you intend to perform on the
detrended image? If it is an FFS (fluorescence fluctuation spectroscopy)
calculation (like number and brightness), choose 'FFS'. If it is an FCS
(fluorescence correlation spectroscopy) calculation (like crosscorrelated
number and brightness or autocorrelation), choose 'FCS'. The difference is
that if 
parallel  Would you like to use multiple cores to speed up this
function? If so, set the number of cores here, or to use all available
cores, use 
tau  The \(tau\) parameter for exponential filtering detrending.
This must be a positive number. Set this to "auto" to use Nolan's algorithm
to automatically find a suitable value for this parameter (recommended).
For multichannel images, it is possible to have a different 
cutoff  In exponential filtering detrending, for the weighted
average, every point gets a weight. This can slow down the computation
massively. However, many of the weights will be approximately zero. With
cutoff, we say that any point with weight less than or equal to 
degree  The degree of the polynomial to use for the polynomial
detrending. This must be a positive integer. Set this to "auto" to use
Nolan's algorithm to automatically find a suitable value for this parameter
(recommended). For multichannel images, it is possible to have a different

The detrended image, an object of class detrended_img.
There are 4 detrending methods available: Robin Hood, boxcar, exponential filtering and polynomial. Robin Hood is described in Nolan et al., 2018. The others are described in Nolan et al., 2017.
Boxcar detrending with parameter \(l\) is a moving average detrending method using a sliding window of size \(2l + 1\).
Exponential filtering detrending is a moving weighted average method where for parameter \(tau\) the weights are calculated as exp\(( t / tau)\) where \(t\) is the distance from the point of interest.
Polynomial detrending works by fitting a polynomial line to a series of points and then correcting the series to remove the trend detailed by this polynomial fit.
Rory Nolan, Luis A. J. Alvarez, Jonathan Elegheert, Maro Iliopoulou, G. Maria Jakobsdottir, Marina RodriguezMuñoz, A. Radu Aricescu, Sergi PadillaParra; nandb—number and brightness in R with a novel automatic detrending algorithm, Bioinformatics, https://doi.org/10.1093/bioinformatics/btx434.
if (FALSE) { ## These examples are not run on CRAN because they take too long. ## You can still try them for yourself. img < ijtiff::read_tif(system.file("extdata", "bleached.tif", package = "detrendr" )) corrected < img_detrend_rh(img) corrected < img_detrend_boxcar(img, "auto", purpose = "fcs", parallel = 2) corrected10 < img_detrend_boxcar(img, 10, purpose = "fcs", parallel = 2) corrected50 < img_detrend_boxcar(img, 50, purpose = "fcs", parallel = 2) corrected < img_detrend_exp(img, "auto", purpose = "ffs", parallel = 2) corrected10 < img_detrend_exp(img, 10, purpose = "ffs", parallel = 2) corrected50 < img_detrend_exp(img, 50, purpose = "fcs", parallel = 2) corrected < img_detrend_polynom(img, "auto", purpose = "ffs", parallel = 2) corrected2 < img_detrend_polynom(img, 2, purpose = "ffs", parallel = 2) }