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 * ImageJ2 software for multidimensional image processing and analysis.
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package net.imagej.ops.features.haralick;

import net.imagej.ops.Ops;
import net.imagej.ops.features.haralick.helper.CoocPXMinusY;
import net.imagej.ops.special.function.Functions;
import net.imagej.ops.special.function.UnaryFunctionOp;
import net.imglib2.IterableInterval;
import net.imglib2.type.numeric.RealType;
import net.imglib2.type.numeric.real.DoubleType;

import org.scijava.plugin.Plugin;

/**
 * 
 * Implementation of Difference Entropy Haralick Feature
 * 
 * @author Andreas Graumann (University of Konstanz)
 * @author Christian Dietz (University of Konstanz)
 * @author Tim-Oliver Buchholz (University of Konstanz)
 */
@Plugin(type = Ops.Haralick.DifferenceEntropy.class, label = "Haralick: Difference Entropy")
public class DefaultDifferenceEntropy<T extends RealType<T>> extends
		AbstractHaralickFeature<T> implements Ops.Haralick.DifferenceEntropy {

	// Avoid log 0
	private static final double EPSILON = Double.MIN_NORMAL;

	private UnaryFunctionOp<double[][], double[]> coocPXMinusYFunc;
	
	@Override
	public void initialize() {
		super.initialize();
		coocPXMinusYFunc = Functions.unary(ops(), CoocPXMinusY.class, double[].class, double[][].class);
	}
	
	@Override
	public void compute(final IterableInterval<T> input, final DoubleType output) {
		final double[][] matrix = getCooccurrenceMatrix(input);

		final double[] pxminusy = coocPXMinusYFunc.calculate(matrix);
		final int nrGrayLevels = matrix.length;

		double res = 0;
		for (int k = 0; k < nrGrayLevels; k++) {
			res += pxminusy[k] * Math.log(pxminusy[k] + EPSILON);
		}

		output.set(-res);

	}

}
