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Why the use of GetPixel and SetPixel is so inefficient!

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8 Jan 2018 1  
Couple of seconds to process a one megapixel picture… what the hell?

The Bitmap class provides two simple methods: GetPixel and SetPixel used respectively to retrieve a point of image (as the Color structure) and set a point of image. The following code illustrates how to retrieve/set all the pixels in a bitmap:

private void GetSetPixel(Bitmap image) {
   for (int x = 0; x < image.Width; x++) {
      for (int y = 0; y < image.Height; y++) {
         Color pixel = image.GetPixel(x, y);
         image.SetPixel(x, y, Color.Black);
      }
   } 
}

As shown, review and modification of pixels is extremely simple. Unfortunately, behind the simplicity of the code lies a serious performance trap. While for a small number of references to image points, the speed at which GetPixel and SetPixel work is good enough, for larger images it is not the case. The graph presented below can serve as a proof of that. It shows the results of 10 tests* which consisted of 10-fold invocation of previously shown GetSetPixel method for images 100x100 and 1000x1000 pixels in size.

Results of speed testing Bitmap's GetPixel and SetPixel methods

 

The average test time for an image measuring 100 by 100 pixels was 543 milliseconds. This speed is acceptable if the image processing is not done frequently. The performance problem is, however, clearly visible when you try to use an image of size 1000 per 1000 pixels. The execution of the test in this case takes an average of more than 41 seconds - more than 4 sec. on a single call to GetSetPixel (seriously!).

Why so slow?

The low efficiency is due to the fact that access to the pixel is not a simple reference to a memory area. Each getting or setting of color is associated with the invocation of a .NET Framework method, which is a wrapper for a native function contained in gdiplus.dll. This call is through the mechanism of P/Invoke (Platform Invocation), which is used to communicate from managed code to unmanaged API (an API outside of the .NET Framework). So for a bitmap of 1000x1000 pixels, there will be 1 million calls to the GetPixel method that besides the validation of parameters uses the native GdipBitmapGetPixel function. Before returning the color information, the GDI+ function has to perform such operations as calculating the position of bytes responsible for the description of the desired pixel… A similar situation occurs in the case of the SetPixel method.

Look at the following code of the Bitmap.GetPixel method obtained with the .NET Reflector (System.Drawing.dll, .NET Framework 2.0):

public Color GetPixel(int x, int y) {
   int argb = 0;
   if ((x < 0) || (x >= base.Width)) {
      throw new ArgumentOutOfRangeException("x", SR.GetString("ValidRangeX"));
   }
   if ((y < 0) || (y >= base.Height)) {
      throw new ArgumentOutOfRangeException("y", SR.GetString("ValidRangeY"));
   }
   
   int status = SafeNativeMethods.Gdip.GdipBitmapGetPixel
    (new HandleRef(this, base.nativeImage), x, y, out argb);
   if (status != 0) {
      throw SafeNativeMethods.Gdip.StatusException(status);
   }
   return Color.FromArgb(argb);
}

Here is the import of the GDI + function:

[DllImport("gdiplus.dll", CharSet=CharSet.Unicode, SetLastError=true, 
ExactSpelling=true)]
internal static extern int GdipBitmapGetPixel(HandleRef bitmap, int x, int y, out int argb);

* I have tested on this laptop: HP Pavilion dv5, AMD Turion X2 Dual-Core Mobile RM-70, 3 GB RAM, Vista Home Premium

Update (2013-07-10): Unfortunately I haven't found time to write an article about a solution to this performance problem but there are some useful hints in my comment.

Update (2013-11-07): I've written an article (...finally) about fast pixel operations. No need to use crappy Get/SetPixel anymore :) Click here.

Update (2018-01-08): If you really want to do some complex and efficient image processing then you should use specialized library like OpenCV. Few months ago I've written "Detecting a Drone - OpenCV in .NET for Beginners (Emgu CV 3.2, Visual Studio 2017)" blog post series that will help you do it...

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