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/*
 * #%L
 * Image processing operations for SciJava Ops.
 * %%
 * Copyright (C) 2014 - 2024 SciJava developers.
 * %%
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 * 
 * 1. Redistributions of source code must retain the above copyright notice,
 *    this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
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 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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package org.scijava.ops.image.threshold.localSauvola;

import net.imglib2.type.logic.BitType;
import net.imglib2.type.numeric.RealType;
import net.imglib2.type.numeric.real.DoubleType;

import org.scijava.function.Computers;
import org.scijava.ops.spi.Nullable;
import org.scijava.ops.spi.OpDependency;

/**
 * 
 * This is a modification of Niblack's thresholding method. In contrast to the
 * recommendation on parameters in the publication, this implementation operates
 * on normalized images (to the [0, 1] range). Hence, the r parameter defaults
 * to half the possible standard deviation in a normalized image, namely 0.5.
 * 
 * 
 * Sauvola J. and Pietaksinen M. (2000) "Adaptive Document Image Binarization"
 * Pattern Recognition, 33(2): 225-236.
 * PDF
 * 
 * 
 * Original ImageJ implementation by Gabriel Landini.
 * 
 *
 * @author Stefan Helfrich (University of Konstanz)
 * @implNote op names='threshold.localSauvola', priority='-100.'
 */
public class ComputeLocalSauvolaThreshold> implements
	Computers.Arity4, T, Double, Double, BitType>
{

	public static final double DEFAULT_K = 0.5;
	public static final double DEFAULT_R = 0.5;

	@OpDependency(name = "stats.mean")
	private Computers.Arity1, DoubleType> meanOp;

	@OpDependency(name = "stats.stdDev")
	private Computers.Arity1, DoubleType> stdDeviationOp;

	/**
	 * TODO
	 *
	 * @param inputNeighborhood
	 * @param inputCenterPixel
	 * @param k
	 * @param r
	 * @param output
	 */
	@Override
	public void compute(final Iterable inputNeighborhood,
		final T inputCenterPixel, @Nullable final Double k,
		@Nullable final Double r, final BitType output)
	{
		compute(inputNeighborhood, inputCenterPixel, k, r, meanOp, stdDeviationOp,
			output);
	}

	public static > void compute(
		final Iterable inputNeighborhood, final T inputCenterPixel, Double k,
		Double r, final Computers.Arity1, DoubleType> meanOp,
		final Computers.Arity1, DoubleType> stdDeviationOp,
		final BitType output)
	{
		if (k == null) k = DEFAULT_K;
		if (r == null) r = DEFAULT_R;

		final DoubleType meanValue = new DoubleType();
		meanOp.compute(inputNeighborhood, meanValue);

		final DoubleType stdDevValue = new DoubleType();
		stdDeviationOp.compute(inputNeighborhood, stdDevValue);

		final double threshold = meanValue.get() * (1.0d + k * ((Math.sqrt(
			stdDevValue.get()) / r) - 1.0));

		output.set(inputCenterPixel.getRealDouble() >= threshold);
	}

}