Nonparametric statistics

Histogram Matching Matlab Code

Histogram matching is a method in image processing of color adjustment of two images using the image histograms.

It is possible to use histogram matching to balance detector responses as a relative detector calibration technique. It can be used to normalize two images, when the images were acquired at the same local illumination (such as shadows) over the same location, but by different sensors, atmospheric conditions or global illumination.

Histogram distances in matlab

The following Matlab project contains the source code and Matlab examples used for histogram distances. This package provides implementations of several commonly used histogram distances: - Kullback-Leibler Divergence - Jenson-Shannon Divergence - Jeffrey Divergence - Chi-Square - Kolmogorov-Smirnov - (Histogram) Intersection - (Histogram) Match - Quadratic form The package comes with an example of color image matching (although this might not be the best application idea, imho; anyway, it showcases the code).

2d weighted histogram in matlab

The following Matlab project contains the source code and Matlab examples used for 2d weighted histogram. This function calculates a 2D, weighted histogram from: (1) an Nx2 matrix of 2D data points (2) an Nx1 vector of weights (3) M_1x1 and M_2x1 grid vectors There is an option to plot the histogram in color using the "bar3c" function (included).

Automatic choice of bin number in regular histogram construction in matlab

The following Matlab project contains the source code and Matlab examples used for automatic choice of bin number in regular histogram construction . Choose automatically the number of bin of a regular histogram using penalized likelihood procedure following paper of Birgé-Rozenholc in ESAIM P&S (2006), 10, pp.24-45 "How many bins should be put in a regular histogram?"

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