Olsen Noise Closer To Working

package com.photoembroidery.tat.olsennoise;


import java.util.Arrays;

/**
 * Created by Tat on 2/17/2015.
 */

public class OlsenNoise2D {

    public static void convolve(int[] pixels, int offset, int stride, int x, int y, int width, int height, int[][] matrix, int parts) {
        int startIndex = x + (y * stride);
        int lastIndex = (x + width - 1) + ((y + height - 1) * stride);
        int x_pos = x;
        int y_pos = y;
        int indexInc = 1;
        int yinc = 0;
        int xinc = 1;

        for (int i = 0, s = width + height; i < s; i++) {
            if (i == width) {
                indexInc = stride;
                yinc = 1;
                xinc = 0;
            }
            int x_counter = x_pos;
            int index = startIndex;
            while (x_counter >= x && index <= lastIndex) {
                pixels[offset + index] = convolve(pixels, stride, offset + index, matrix, parts);
                x_counter--;
                index += stride - 1;
            }
            startIndex += indexInc;
            x_pos += xinc;
            y_pos += yinc;
        }
    }


    private static int crimp(int color) {
        return (color >= 0xFF) ? 0xFF : (color < 0) ? 0 : color;
    }

    private static int convolve(int[] pixels, int stride, int index, int[][] matrix, int parts) {
        int redSum = 0;
        int greenSum = 0;
        int blueSum = 0;
        int pixel, factor;
        for (int j = 0, m = matrix.length; j < m; j++, index++) {
            for (int k = 0, n = matrix[j].length, q = index; k < n; k++, q += stride) {
                pixel = pixels[q];
                factor = matrix[j][k];
                redSum += factor * ((pixel >> 16) & 0xFF);
                greenSum += factor * ((pixel >> 8) & 0xFF);
                blueSum += factor * ((pixel) & 0xFF);
            }
        }
        return 0xFF000000 | ((crimp(redSum / parts) << 16) | (crimp(greenSum / parts) << 8) | (crimp(blueSum / parts)));
    }

    //occupies same footprint
    private void applyNoise(int[] pixels, int stride, int x_within_field, int y_within_field, int width, int height, int iteration) {
        int index = 0;
        for (int k = 0, n =  height - 1; k <= n; k++, index += stride) {
            for (int j = 0, m = width - 1; j <= m; j++) {
                int current = index + j;
                pixels[current] += (hashrandom(x_within_field + j, y_within_field + k, iteration) & (1 << (7 - iteration)));
            }
        }
    }

    //requires half the height and width be good.
    private void applyScale(int[] pixels, int stride, int width, int height) {
        int index = (height - 1) * stride;
        for (int k = 0, n = 0 + height - 1; k <= n; n--, index -= stride) {
            for (int j = 0, m = width - 1; j <= m; m--) {
                int current = index + m;
                int lower = ((n / 2) * stride) + (m / 2);
                pixels[current] = pixels[lower];
            }
        }
    }


    //requires width + 1 valid, height + 1
    private static final int[][] blur2x2 = new int[][]{
            {1, 1},
            {1, 1},
    };

    private void applyBlur(int[] pixels, int stride, int width, int height) {
        convolve(pixels, 0, stride,0,0, width, height, blur2x2, 4);
    }

    //You need to give it an array larger than the current one. This math is just a guess at a number big enough, it's not actually the max dim the array would properly need to be.
    public int getRequiredDim(int dim) {
        return (dim + 5) * 2;
    }
    private void trim(int[] pixels, int width, int height, int[] workingpixels, int workingstride) {
        for (int k = 0; k < height; k++) {
            for (int j = 0; j < width; j++) {
                int index = j + (k * width);
                int workingindex = j + (k * workingstride);
                pixels[index] = workingpixels[workingindex];
            }
        }
    }

    static final int maxiterations = 7;
    public void olsennoise(int[] pixels, int stride, int x, int y, int width, int height) {
        Arrays.fill(pixels, 0xFF000000);
        olsennoise(pixels, stride, x, y, width, height, maxiterations);
    }

    public void olsennoise(int[] pixels, int stride, int x_within_field, int y_within_field, int width, int height, int iteration) {
        if (iteration == 0) {
            applyNoise(pixels, stride, x_within_field, y_within_field, width, height, iteration);
            return;
        }

        olsennoise(pixels, stride, (x_within_field/2)-2, (y_within_field/2)-2, (width/2)+2, (height/2) + 2, iteration - 1);

        //scale only requires (width/2+1) and (height/2+1) valid pixels.
        applyScale(pixels, stride, width+1, height+1);

        //blur only requires width+1 and height+1 valid pixels.
        applyBlur(pixels, stride, width, height);

        //noise requires width, and height valid pixels
        applyNoise(pixels, stride, x_within_field, y_within_field, width, height, iteration);
    }


    public static int hashrandom(int... elements) {
        long hash = 0;
        for (int i = 0; i < elements.length; i++) {
            hash ^= elements[i];
            hash = hash(hash);
        }
        return (int) hash;
    }

    public static long hash(long v) {
        long hash = v;
        long h = hash;

        switch ((int) hash & 3) {
            case 3:
                hash += h;
                hash ^= hash << 32;
                hash ^= h << 36;
                hash += hash >> 22;
                break;
            case 2:
                hash += h;
                hash ^= hash << 22;
                hash += hash >> 34;
                break;
            case 1:
                hash += h;
                hash ^= hash << 20;
                hash += hash >> 2;
        }
        hash ^= hash << 6;
        hash += hash >> 10;
        hash ^= hash << 8;
        hash += hash >> 34;
        hash ^= hash << 50;
        hash += hash >> 12;
        return hash;
    }
}