/// <summary>
/// Calculates Shannon entropy for one image by grouppping bytes by channels
/// </summary>
/// <param name="image"></param>
/// <returns></returns>
public static double ShannonEntropyByChannels(Image <Bgr, byte> image)
{
int size = image.Rows * image.Cols;
byte[] data = new byte[size * image.NumberOfChannels];
for (int m = 0; m < image.Rows; m++)
{
for (int n = 0; n < image.Cols; n++)
{
Bgr p = image[m, n];
data[0 + m * image.Cols + n] = (byte)p.Blue;
data[size + m * image.Cols + n] = (byte)p.Green;
data[2 * size + m * image.Cols + n] = (byte)p.Red;
}
}
// for each channel
//var channels = ImageHelper.GetBgrChannelsAsByte(image);
//double SE_B = (new DataEntropyUTF8(channels.B)).Entropy;
//double SE_G = (new DataEntropyUTF8(channels.G)).Entropy;
//double SE_R = (new DataEntropyUTF8(channels.R)).Entropy;
//double SE_AVG = (SE_B + SE_G + SE_R) / 3.0;
var SE = new DataEntropyUTF8(data);
return(SE.Entropy);
}
/// <summary>
/// Calculates Shannon entropy for image1 and image2. Retuns entropy defference of image2 and image1
/// Positive value means enchacement (of contrast, visibility etc) in image2 comparing to image1. Negative - degradation.
/// </summary>
/// <param name="image1"></param>
/// <param name="image2"></param>
/// <returns></returns>
//public static double ShannonEntropyDiff(Image<Gray, byte> image1, Image<Gray, byte> image2)
//{
// var SE1 = new DataEntropyUTF8(image1);
// var SE2 = new DataEntropyUTF8(image2);
// double result = SE2.Entropy - SE1.Entropy;
// return result;
//}
/// <summary>
/// Calculates Shannon entropy for image1 and image2. Retuns entropy defference of image2 and image1
/// Positive value means enchacement (of contrast, visibility etc) in image2 comparing to image1. Negative - degradation.
/// </summary>
/// <param name="image1"></param>
/// <param name="image2"></param>
/// <returns></returns>
public static double ShannonEntropyDiff(Image <Bgr, byte> image1, Image <Bgr, byte> image2)
{
// compute for while image at once (possible can cause invalid result)
//var SE1 = new DataEntropyUTF8(image1);
//var SE2 = new DataEntropyUTF8(image2);
//double result = SE2.Entropy - SE1.Entropy;
//return result;
// compute for each channel separately
var channels1 = image1.Split();
var channels2 = image2.Split();
double averagedEntropy1 = 0;
double averagedEntropy2 = 0;
for (int i = 0; i < channels1.Count(); i++)
{
var SE1 = new DataEntropyUTF8(channels1[i]);
var SE2 = new DataEntropyUTF8(channels2[i]);
averagedEntropy1 += SE1.Entropy;
averagedEntropy2 += SE2.Entropy;
}
averagedEntropy1 = averagedEntropy1 / channels1.Count();
averagedEntropy2 = averagedEntropy2 / channels2.Count();
double result = averagedEntropy2 - averagedEntropy1;
return(result);
}
/// <summary>
/// Calculates Shannon entropy for one image
/// </summary>
/// <param name="image"></param>
/// <returns></returns>
public static double ShannonEntropy(Image <Bgr, byte> image)
{
var SE = new DataEntropyUTF8(image);
return(SE.Entropy);
}
