contrast.hpp File Reference

#include <memory_resource>
#include <nk/value/span.hpp>
#include <nk/value/value.hpp>
#include <string>
#include <tuple>

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Classes
struct	nk::image::AdaptHistEqOptions
	Parameters for adapthisteq. More...

Functions
std::tuple< Value, Value >	nk::image::imhist (const Value &I, int n, std::pmr::memory_resource *mr=nullptr)
	Image histogram ([counts, bin_centers] = imhist(I, n)).
Value	nk::image::stretchlim (const Value &I, double low_tol, double high_tol, std::pmr::memory_resource *mr=nullptr)
	Stretch limits from saturation tolerances (lim = stretchlim(I, [low_tol, high_tol])).
Value	nk::image::imadjust (const Value &I, double low_in, double high_in, double low_out, double high_out, double gamma, std::pmr::memory_resource *mr=nullptr)
	Affine intensity remap with optional gamma (J = imadjust(...)).
Value	nk::image::adaptthresh (const Value &I, double sensitivity, int neighborhood, const std::string &statistic, std::pmr::memory_resource *mr=nullptr)
	Locally adaptive threshold matrix (T = adaptthresh(I, ...)).
Value	nk::image::histeq (const Value &I, int n, std::pmr::memory_resource *mr=nullptr)
	Histogram equalisation (J = histeq(I, n)).
Value	nk::image::adapthisteq (const Value &I, const AdaptHistEqOptions &opts={}, std::pmr::memory_resource *mr=nullptr)
	Contrast Limited Adaptive Histogram Equalisation (J = adapthisteq(I, opts)).
std::tuple< Value, Value >	nk::image::graythresh (const Value &I, std::pmr::memory_resource *mr=nullptr)
	Otsu's threshold and effectiveness metric ([level, em] = graythresh(I)).
std::tuple< Value, Value >	nk::image::otsuthresh (const Value &counts, std::pmr::memory_resource *mr=nullptr)
	Otsu's threshold from a precomputed histogram ([level, em] = otsuthresh(counts)).
std::tuple< Value, Value >	nk::image::multithresh (const Value &I, int N, std::pmr::memory_resource *mr=nullptr)
	N-level Otsu ([thresh, em] = multithresh(I, N)).
Value	nk::image::imbinarize (const Value &I, double thresh, std::pmr::memory_resource *mr=nullptr)
	Threshold an image (BW = imbinarize(I, thresh)).
Value	nk::image::imbinarize (const Value &I, const Value &T, std::pmr::memory_resource *mr=nullptr)
	Per-pixel threshold (BW = imbinarize(I, T)).
Value	nk::image::imquantize (const Value &I, const Value &levels, std::pmr::memory_resource *mr=nullptr)
	Quantise into N+1 classes (L = imquantize(I, levels)).
Value	nk::image::imhistmatch (const Value &I, const Value &ref, int nbins, Value *hgramOut=nullptr, std::pmr::memory_resource *mr=nullptr)
	Histogram matching to a reference image ([J, hgram] = imhistmatch(I, ref, nbins)).
Value	nk::image::imflatfield (const Value &I, double sigma, const Value &mask, std::pmr::memory_resource *mr=nullptr)
	Flat-field correction (J = imflatfield(I, sigma, mask)).
Value	nk::image::wcodemat (const Value &X, int nb, const std::string &opt, int absol, std::pmr::memory_resource *mr=nullptr)
	Wavelet-display quantisation (Y = wcodemat(X, nb, opt, absol)).
Value	nk::image::entropy (const Value &I, int nbins, std::pmr::memory_resource *mr=nullptr)
	Shannon entropy of the image histogram (H = entropy(I, nbins)).
Value	nk::image::grayslice (const Value &I, int N, std::pmr::memory_resource *mr=nullptr)
	Multilevel thresholding into an indexed image, level-count form (L = grayslice(I, N)).
Value	nk::image::grayslice (const Value &I, Span< const double > levels, std::pmr::memory_resource *mr=nullptr)
	Multilevel thresholding into an indexed image, explicit thresholds form (L = grayslice(I, [t1, t2, …])).