public WTStipple(Image source, WangTileSet tileSet, int tonalRange, Bitmap dest)
{
// Convert source image to grayscale
Bitmap bmp = new Bitmap(source.Width, source.Height);
Graphics g = Graphics.FromImage(bmp);
g.DrawImage(source, new Rectangle(0, 0, source.Width, source.Height));
float[,] grayscale = ToDensity(bmp);
this.tileSet = tileSet;
// Subdivide image recusively as long as we need more density on each leave's tile
// to account for the underlying sampled region on the image
ImageTreeNode root = new ImageTreeNode();
Random r = new Random(tileSet.tiles.Count);
root.tile = r.Next(tileSet.tiles.Count);
Rectangle rect = new Rectangle(0, 0, bmp.Width, bmp.Height);
int minSize = 8;
Graphics g2 = Graphics.FromImage(dest);
g2.Clear(Color.White);
Refine_r(root, rect, grayscale, minSize, 0, 5, tonalRange, dest);
}
public WTStipple(Image source, WangTileSet tileSet, int tonalRange, Bitmap dest )
{
// Convert source image to grayscale
Bitmap bmp = new Bitmap(source.Width, source.Height);
Graphics g = Graphics.FromImage(bmp);
g.DrawImage(source, new Rectangle(0, 0, source.Width, source.Height));
float[,] grayscale = ToDensity(bmp);
this.tileSet = tileSet;
// Subdivide image recusively as long as we need more density on each leave's tile
// to account for the underlying sampled region on the image
ImageTreeNode root = new ImageTreeNode();
Random r = new Random(tileSet.tiles.Count);
root.tile = r.Next(tileSet.tiles.Count);
Rectangle rect = new Rectangle(0, 0, bmp.Width, bmp.Height);
int minSize = 8;
Graphics g2 = Graphics.FromImage(dest);
g2.Clear(Color.White);
Refine_r(root, rect, grayscale, minSize, 0, 5, tonalRange, dest );
}
private void Refine_r(ImageTreeNode node, Rectangle rect, float[,] density, int minSize, int depth, int maxDepth, int toneScale, Bitmap dest)
{
Debug.Assert(node.tile != -1);
List<PoissonDist.PoissonSample> distribution = tileSet.tiles[node.tile].distribution;
float tileMaxDensity = (float)distribution.Count;
float requiredDensity = AreaDensity(density, rect);
// Cover the area with the current tile
float tileAvgDensity = Math.Min(1.0f, tileMaxDensity / (rect.Width * rect.Height));
for (int i = 0; i < distribution.Count; i++)
{
int stippleX = rect.Left + (int)(rect.Width * distribution[i].x);
int stippleY = rect.Top + (int)(rect.Height * distribution[i].y);
float r = 1;//Math.Max(1, (distribution[i].radius * rect.Width));
float area = (float)(r*r * Math.PI);
float diskDensity = DiskDensity(density, new Point(stippleX, stippleY), (int)r);
float diskAvgDensity = diskDensity / area;
float factor = (float)(0.1f / Math.Pow(1, -2) * Math.Pow(4, 2.0f * depth) / toneScale);
if (diskAvgDensity < (float)i * factor) continue;
dest.SetPixel(stippleX, stippleY, Color.Black);
}
// Check whether we need to keep subdividing
if (rect.Width <= minSize || rect.Height <= minSize || depth == maxDepth) return;
if (Math.Pow(0.1, -2) / Math.Pow(4, 2 * depth) * toneScale - tileMaxDensity > 16 * tileMaxDensity )
{
// we need to subdivide
int[,] subd;
int splitsPerDimension;
tileSet.GetSubdivisions(node.tile, out subd, out splitsPerDimension);
node.children = new ImageTreeNode[splitsPerDimension, splitsPerDimension];
Size childRectSize = new Size((int)Math.Floor((float)rect.Width / splitsPerDimension),
(int)Math.Floor((float)rect.Height / splitsPerDimension));
for (int j = 0; j < splitsPerDimension; j++)
{
for (int i = 0; i < splitsPerDimension; i++)
{
node.children[i, j] = new ImageTreeNode();
node.children[i, j].tile = subd[i, j];
Rectangle childRect = new Rectangle(rect.X + i * childRectSize.Width,
rect.Y + j * childRectSize.Height,
childRectSize.Width,
childRectSize.Height);
if (i == splitsPerDimension - 1) // adjust borders
childRect.Width = rect.Right - childRect.X;
if (j == splitsPerDimension - 1) // adjust borders
childRect.Height = rect.Bottom - childRect.Y;
Refine_r(node.children[i, j], childRect, density, minSize, depth + 1, maxDepth, toneScale, dest);
}
}
}
}
private void Refine_r(ImageTreeNode node, Rectangle rect, float[,] density, int minSize, int depth, int maxDepth, int toneScale, Bitmap dest)
{
Debug.Assert(node.tile != -1);
List <PoissonDist.PoissonSample> distribution = tileSet.tiles[node.tile].distribution;
float tileMaxDensity = (float)distribution.Count;
float requiredDensity = AreaDensity(density, rect);
// Cover the area with the current tile
float tileAvgDensity = Math.Min(1.0f, tileMaxDensity / (rect.Width * rect.Height));
for (int i = 0; i < distribution.Count; i++)
{
int stippleX = rect.Left + (int)(rect.Width * distribution[i].x);
int stippleY = rect.Top + (int)(rect.Height * distribution[i].y);
float r = 1;//Math.Max(1, (distribution[i].radius * rect.Width));
float area = (float)(r * r * Math.PI);
float diskDensity = DiskDensity(density, new Point(stippleX, stippleY), (int)r);
float diskAvgDensity = diskDensity / area;
float factor = (float)(0.1f / Math.Pow(1, -2) * Math.Pow(4, 2.0f * depth) / toneScale);
if (diskAvgDensity < (float)i * factor)
{
continue;
}
dest.SetPixel(stippleX, stippleY, Color.Black);
}
// Check whether we need to keep subdividing
if (rect.Width <= minSize || rect.Height <= minSize || depth == maxDepth)
{
return;
}
if (Math.Pow(0.1, -2) / Math.Pow(4, 2 * depth) * toneScale - tileMaxDensity > 16 * tileMaxDensity)
{
// we need to subdivide
int[,] subd;
int splitsPerDimension;
tileSet.GetSubdivisions(node.tile, out subd, out splitsPerDimension);
node.children = new ImageTreeNode[splitsPerDimension, splitsPerDimension];
Size childRectSize = new Size((int)Math.Floor((float)rect.Width / splitsPerDimension),
(int)Math.Floor((float)rect.Height / splitsPerDimension));
for (int j = 0; j < splitsPerDimension; j++)
{
for (int i = 0; i < splitsPerDimension; i++)
{
node.children[i, j] = new ImageTreeNode();
node.children[i, j].tile = subd[i, j];
Rectangle childRect = new Rectangle(rect.X + i * childRectSize.Width,
rect.Y + j * childRectSize.Height,
childRectSize.Width,
childRectSize.Height);
if (i == splitsPerDimension - 1) // adjust borders
{
childRect.Width = rect.Right - childRect.X;
}
if (j == splitsPerDimension - 1) // adjust borders
{
childRect.Height = rect.Bottom - childRect.Y;
}
Refine_r(node.children[i, j], childRect, density, minSize, depth + 1, maxDepth, toneScale, dest);
}
}
}
}
