Image Transformation: Grayscale to Color

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Introduction  

This is an easy algorithm of image transformation from grayscale image to color. It's far from ideal, but it is very simple.

Background

Usually we calculate gray color as:

Gray  = Green * 0.59 + Blue * 0.30 + Red * 0.11;

Each color with structure [Gray, Gray, Gray] has a set of colors:

G = [Gray, Gray, Gray]<br />G -> P = {C}, for each C from P:  Green * 0.59 + Blue * 0.30 + Red * 0.11 = Gray.

First of all, we create a set of control points. Control point is equivalent of "gray" color and "full" color. When we have control points set, we can approximate any "gray" color to "full" color. If "gray" color is located between two control points C1 and C2, then the color approximates as:

K = (Gray - C1<sub>Gray</sub>)/(C2<sub>Gray </sub>- C1<sub>Gray</sub>)<br />Red = C1<sub>Red </sub>+ K*(C2<sub>Red </sub>- C1<sub>Red</sub>)<br />Green = C1<sub>Green </sub>+ K*(C2<sub>Green </sub>- C1<sub>Green</sub>)<br />Blue = C1<sub>Blue </sub>+ K*(C2.<sub>Blue </sub>- C1<sub>Blue</sub>)

Now we has "full color" equivalent for each "gray" color.

Using the Code  

ControlPoint is a structure for storing data about control points.

public struct ControlPoint
{
    private int level;
     public int Level
    {
        get { return level; }
        set { level = value; }
    }
    private Color color;
     public Color Color
    {
        get { return color; }
        set { color = value; }
    }
     public ControlPoint(int level, Color color)
    {
        this.color = color;
        this.level = level;
    }
     public override string ToString()
    {
        return "Level: " + level.ToString() + "; Color: " + color.ToString();
    }
} 

PointsComparer is a class for comparing two control points:

public class PointsComparer: IComparer<ControlPoint>
{
    #region IComparer<ControlPoint> Members
     public int Compare(ControlPoint x, ControlPoint y)
    {
        if (x.Level > y.Level)
        {
            return 1;
        }
        if (x.Level < y.Level)
        {
            return -1;
        }
        return 0;
    }
     #endregion
} 

ColorBuilder is a class for building a color diagram. It returns an array of 256 colors - our diagram.

public static Color[] GetColorDiagram(List<ControlPoint> points)
{
    Color[] colors = new Color[256];
    points.Sort(new PointsComparer());
     for (int i = 0; i < 256; i++)
    {
        ControlPoint leftColor = new ControlPoint
				(0, GetNearestLeftColor(points[0].Color)); 
        ControlPoint rightColor = new ControlPoint
			(255, GetNearestRigthColor(points[points.Count - 1].Color));
        if (i < points[0].Level)
        {
            rightColor = points[0];
        }
        if (i > points[points.Count - 1].Level)
        {
            leftColor = points[points.Count - 1];
        }
        else
        {
            for (int j = 0; j < points.Count - 1; j++)
            {
                if ((points[j].Level <= i) & (points[j + 1].Level > i))
                {
                    leftColor = points[j];
                    rightColor = points[j + 1];
                }
            }
        }
        if ((rightColor.Level - leftColor.Level) != 0)
        {
            double koef = (double)(i - leftColor.Level) / 
			(double)(rightColor.Level - leftColor.Level);
            int r = leftColor.Color.R + (int)(koef * 
			(rightColor.Color.R - leftColor.Color.R));
            int g = leftColor.Color.G + (int)(koef * 
			(rightColor.Color.G - leftColor.Color.G));
            int b = leftColor.Color.B + (int)(koef * 
			(rightColor.Color.B - leftColor.Color.B));
            colors[i] = Color.FromArgb(r, g, b);
        }
        else
        {
            colors[i] = leftColor.Color;
        }
     }
     return colors;
} 

Now we can get the color image:

colorBitmap = new Bitmap(sourceBitmap);
for (int i = 0; i < sourceBitmap.Width; i++)
{
    for (int j = 0; j < sourceBitmap.Height; j++)
    {
        int level = sourceBitmap.GetPixel(i, j).B;
        colorBitmap.SetPixel(i, j, colors[level]);
    }
}
pbxColorImage.Image = colorBitmap;

Points of Interest  

The algorithms is very easy, and has many defects. But it is a good example for beginners in image processing. 

Update Information

1. New formula for grayscale level calculation
2. Bug with empty list was removed

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)