Convolution.java

/*
 * (C) Copyright 2016-2017 JOML

 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal
 in the Software without restriction, including without limitation the rights
 to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
 copies of the Software, and to permit persons to whom the Software is
 furnished to do so, subject to the following conditions:

 The above copyright notice and this permission notice shall be included in
 all copies or substantial portions of the Software.

 THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
 IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
 FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
 AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
 LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
 OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
 THE SOFTWARE.

 */
package org.joml.sampling;

//#ifdef __HAS_NIO__
import java.nio.FloatBuffer;
//#endif

import org.joml.Math;

/**
 * Generates various convolution kernels.
 *
 * @author Kai Burjack
 */
public class Convolution {

//#ifdef __HAS_NIO__
    /**
     * Generate a Gaussian convolution kernel with the given number of rows and columns, and store
     * the factors in row-major order in <code>dest</code>.
     *
     * @param rows
     *          the number of rows (must be an odd number)
     * @param cols
     *          the number of columns (must be an odd number)
     * @param sigma
     *          determines how big the factors are at the center of distribution
     * @param dest
     *          will hold the kernel factors in row-major order
     */
    public static void gaussianKernel(int rows, int cols, float sigma, FloatBuffer dest) {
        if ((rows & 1) == 0) {
            throw new IllegalArgumentException("rows must be an odd number");
        }
        if ((cols & 1) == 0) {
            throw new IllegalArgumentException("cols must be an odd number");
        }
        if (dest == null) {
            throw new IllegalArgumentException("dest must not be null");
        }
        if (dest.remaining() < rows * cols) {
            throw new IllegalArgumentException("dest must have at least " + (rows * cols) + " remaining values");
        }
        float sum = 0.0f;
        int pos = dest.position();
        for (int i = 0, y = -(rows - 1) / 2; y <= (rows - 1) / 2; y++) {
            for (int x = -(cols - 1) / 2; x <= (cols - 1) / 2; x++, i++) {
                float k = (float) Math.exp(-(y * y + x * x) / (2.0 * sigma * sigma));
                dest.put(pos + i, k);
                sum += k;
            }
        }
        for (int i = 0; i < rows * cols; i++) {
            dest.put(pos + i, dest.get(pos + i) / sum);
        }
    }
//#endif

    /**
     * Generate a Gaussian convolution kernel with the given number of rows and columns, and store
     * the factors in row-major order in <code>dest</code>.
     *
     * @param rows
     *          the number of rows (must be an odd number)
     * @param cols
     *          the number of columns (must be an odd number)
     * @param sigma
     *          determines how big the factors are at the center of distribution
     * @param dest
     *          will hold the kernel factors in row-major order
     */
    public static void gaussianKernel(int rows, int cols, float sigma, float[] dest) {
        if ((rows & 1) == 0) {
            throw new IllegalArgumentException("rows must be an odd number");
        }
        if ((cols & 1) == 0) {
            throw new IllegalArgumentException("cols must be an odd number");
        }
        if (dest == null) {
            throw new IllegalArgumentException("dest must not be null");
        }
        if (dest.length < rows * cols) {
            throw new IllegalArgumentException("dest must have at least " + (rows * cols) + " remaining values");
        }
        float sum = 0.0f;
        for (int i = 0, y = -(rows - 1) / 2; y <= (rows - 1) / 2; y++) {
            for (int x = -(cols - 1) / 2; x <= (cols - 1) / 2; x++, i++) {
                float k = (float) Math.exp(-(y * y + x * x) / (2.0 * sigma * sigma));
                dest[i] = k;
                sum += k;
            }
        }
        for (int i = 0; i < rows * cols; i++) {
            dest[i] = dest[i] / sum;
        }
    }

}