Olsen Noise Algorithm C++ WIP (Working copy).

/*
 * Original Author @author Tat
 * Mod code Vivienne Anthony
 * c++ rewrite vivienne (WIP)
 * verion 1.0 Functional Rewrite
 *
 * Changes
 *  Java to C++ conversion
 *  Memory pointer usage
 */

#include <iostream>
#include <vector>

#include <stdio.h>
#include <stdlib.h>
#include <png++/png.hpp>

using namespace std;

void SaveTerrFile(const int * image, int size, char * filename);


class OlsenNoise2D
{

public:
    int * olsennoise(int x, int y, int width, int height);

private:
    int hashrandom(std::vector<long long int> elements);
    long long hash(long long v);

};

int * OlsenNoise2D::olsennoise(int x, int y, int width, int height)
{
    int maxiterations = 7;
    int cx, cy;
    int cxh, cyh;
    int cwidth, cheight;
    int xoff, yoff;
    int nwidth, nheight;
    int nx, ny;
    int nxh, nyh;
    int m=0;
    int n=0;
    int fieldwidth=0;
    int fieldheight=0;

    int * field = NULL;

    for (int iteration = 0; iteration < maxiterations; iteration++)
    {
        nx = x;
        ny = y;

        nxh = x + width;
        nyh = y + height;

        for (int i = 1,n = maxiterations - iteration; i < n; i++)
        {
            nx = (nx / 2) - 1;
            ny = (ny / 2) - 1;
            nxh = 1 -(-nxh/2);
            nyh = 1 -(-nyh/2);
        }

        xoff = -2*((nx/2)) + nx + 1;
        yoff = -2*((ny/2)) + ny + 1;

        cx = (nx / 2) - 1;
        cy = (ny / 2) - 1;
        cxh = 1 -(-nxh/2);
        cyh = 1 -(-nyh/2);

        nwidth = nxh - nx;
        nheight = nyh - ny;

        cwidth = cxh - cx;
        cheight = cyh - cy;

        /// rest
        fieldwidth=cwidth;
        fieldheight=cheight;

        /// Only happens once
        if (field==NULL)
        {
            /// allocate memory
            field = new int[cheight * cwidth];

            /// blank value
            for (int x = 0; x < cwidth; x++)
            {
                for (int y = 0; y < cheight; y++)
                {
                    field[x+(y*cwidth)]=0;
                }
            }
        }

        /// First loop
        for (int j = 0, m=cwidth; j < m; j++)
        {
            for (int k = 0, n=cheight; k < n; k++)
            {
                field[j+(k*m)] += (hashrandom( {cx + j, cy + k, iteration}) & (1 << (7 - iteration)));
            }
        }

        /// Up sampled
        int * upsampled = new int[(fieldwidth*2)*(fieldheight*2)];
        long int upsampledsize=(fieldwidth*2)*(fieldheight*2);

        for (int j = 0, m=fieldwidth*2; j < m; j++)
        {
            for (int k = 0,n=fieldheight*2; k < n; k++)
            {
                upsampled[j+(k*m)] = field[(j / 2)+((k / 2)*fieldwidth)];
            }
        }

        /// Allocate upsampled to field
        delete [] field;
        field = upsampled;

        /// Copy new fieldwieght and fieldheight
        fieldwidth=fieldwidth*2;
        fieldheight=fieldheight*2;

        /// Blur field
        int * blurfield =new int[(fieldwidth-2)*(fieldheight-2)];
        long int blurfieldsize = (fieldwidth-2)*(fieldheight-2);

        for (int j = 0,m=fieldwidth-2; j < m; j++)
        {
            for (int k = 0, n=fieldheight-2;  k < n; k++)
            {
                for (int h = 0; h < 9; h++)
                {
                    blurfield[j+(k*m)] += field[(j + (h % 3))+((k+(h/ 3))*fieldwidth)];
                }
                blurfield[j+(k*m)] /= 9;
            }
        }

        /// Allocate blurfield to field
        delete [] field;
        field = blurfield;

        /// Copy new fieldwieght and fieldheight
        fieldwidth=fieldwidth-2;
        fieldheight=fieldheight-2;

        /// Trim field
        int * trimfield = new int[nwidth*nheight];
        long int trimfieldsize = nwidth*nheight;

        for (int j = 0, m=nwidth; j < m; j++)
        {
            for (int k = 0, n=nheight; k < n; k++)
            {
                trimfield[j+(k*m)] = field[(j + xoff)+((k + yoff)*fieldwidth)];
            }
        }

        /// Allocate trimfield to field
        delete [] field;
        field = trimfield;

    }

    return field;
}

int OlsenNoise2D::hashrandom(std::vector<long long int> elements)
{
    long long hashcalc = 0;


    for (int i = 0; i < elements.size(); i++)
    {
        hashcalc ^= elements[i];
        hashcalc = hash(hashcalc);
    }
    return (int) hashcalc;
};

long long OlsenNoise2D::hash(long long v)
{
    long long hash = v;
    long 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;
};


int main()
{
    /// Test
    int ImageSize=2049;
    int * imageInput = new int[ImageSize*ImageSize];

    /// Image
    OlsenNoise2D testingolsen;
    imageInput=testingolsen.olsennoise(0,0,ImageSize,ImageSize);

    SaveTerrFile(imageInput, ImageSize, "output.png");

    delete imageInput;http://pastebin.com/1i0vwJgv

    return 1;
}


void SaveTerrFile(const int * image, int size, char * filename)
{
    png::image< png::rgb_pixel > newimage(size, size);

    for (unsigned int y = 0; y < newimage.get_width(); ++y)
    {
        for (unsigned int x = 0; x < newimage.get_height(); ++x)
        {
            int col = int(image[x+(y*newimage.get_width())]);
            newimage[y][x] = png::rgb_pixel(col,col,col);
            // non-checking equivalent of image.set_pixel(x, y, ...);
        }
    }

    newimage.write(filename);
}