public virtual ImageDescription filter(ImageDescription inputImage)
{
inputImage.computeGrayscale();
int imageSizeX = inputImage.sizeX;
int imageSizeY = inputImage.sizeY;
byte[,] inputGray = inputImage.gray;
byte[,] outputGray = new byte[imageSizeY, imageSizeX];
// 1. Gauss
float[,] gaussConvolutionMatrix = FilterBankUtil.generateNormalizedGaussConvolutionMatrix(sigma, 5);
float[,] gaussResult = ImageDescriptionUtil.mirroredMarginConvolution(inputGray, gaussConvolutionMatrix);
// 2. Gradient
float[,] dx = ImageDescriptionUtil.mirroredMarginConvolution(gaussResult, FilterBankUtil.normalizedSobelX);
float[,] dy = ImageDescriptionUtil.mirroredMarginConvolution(gaussResult, FilterBankUtil.normalizedSobelY);
// 3. Gradient Amplitude
float[,] amplitudeResult = new float[imageSizeY, imageSizeX];
for (int i = 0; i < imageSizeY; i++)
{
for (int j = 0; j < imageSizeX; j++)
{
amplitudeResult[i, j] = (float)Math.Sqrt(dx[i, j] * dx[i, j] + dy[i, j] * dy[i, j]);
}
}
for (var i = 0; i < imageSizeY; i++)
{
for (var j = 0; j < imageSizeX; j++)
{
if (amplitudeResult[i, j] < 255)
{
outputGray[i, j] = (byte)(amplitudeResult[i, j] + 0.5f);
}
else
{
outputGray[i, j] = 255;
}
}
}
ImageDescription outputImage = new ImageDescription();
outputImage.sizeX = imageSizeX;
outputImage.sizeY = imageSizeY;
foreach (ColorChannelEnum colorChannel in Enum.GetValues(typeof(ColorChannelEnum)))
{
outputImage.setColorChannel(colorChannel, inputImage.getColorChannel(colorChannel));
}
outputImage.setColorChannel(ColorChannelEnum.Sobel, outputGray);
return(outputImage);
}
public virtual ImageDescription filter(ImageDescription inputImage)
{
return(ImageDescriptionUtil.mirroredMarginConvolution(inputImage, colorChannelsToFilter, convolutionMatrix));
}
public virtual ImageDescription filter(ImageDescription inputImage)
{
inputImage.computeGrayscale();
int imageSizeX = inputImage.sizeX;
int imageSizeY = inputImage.sizeY;
byte[,] inputGray = inputImage.gray;
byte[,] outputGray = new byte[imageSizeY, imageSizeX];
float[,] gaussConvolutionMatrix = FilterBankUtil.generateNormalizedGaussConvolutionMatrix(sigma, 7);
float[,] gaussResult = ImageDescriptionUtil.mirroredMarginConvolution(inputGray, gaussConvolutionMatrix);
List <float[, ]> templates = FilterBankUtil.normalizedKirschTemplates;
List <float[, ]> results = new List <float[, ]>(templates.Count);
foreach (float[,] template in templates)
{
results.Add(ImageDescriptionUtil.mirroredMarginConvolution(gaussResult, template));
}
float[,] amplitudeResult = new float[imageSizeY, imageSizeX];
int[,] anglesResult = new int[imageSizeY, imageSizeX];
for (int i = 0; i < imageSizeY; i++)
{
for (int j = 0; j < imageSizeX; j++)
{
int direction = 0;
float maxValue = 0;
for (int templateIndex = 0; templateIndex < templates.Count; templateIndex++)
{
float value = results[templateIndex][i, j];
if (value > maxValue)
{
maxValue = value;
direction = templateIndex;
}
}
amplitudeResult[i, j] = maxValue;
anglesResult[i, j] = direction;
}
}
if (!applyNms)
{
for (var i = 0; i < imageSizeY; i++)
{
for (var j = 0; j < imageSizeX; j++)
{
if (amplitudeResult[i, j] < 255)
{
outputGray[i, j] = (byte)(amplitudeResult[i, j] + 0.5f);
}
else
{
outputGray[i, j] = 255;
}
}
}
}
else
{
float[,] nmsResult = new float[imageSizeY, imageSizeX];
for (int i = 0; i < imageSizeY; i++)
{
for (int j = 0; j < imageSizeX; j++)
{
int angle = anglesResult[i, j];
if (angle == 2 || angle == 6)
{
if ((i == 0 || amplitudeResult[i, j] >= amplitudeResult[i - 1, j]) &&
(i == imageSizeY - 1 || amplitudeResult[i, j] > amplitudeResult[i + 1, j]))
{
nmsResult[i, j] = amplitudeResult[i, j];
}
}
else
{
if (angle == 1 || angle == 5)
{
if ((i == 0 || j == imageSizeX - 1 || amplitudeResult[i, j] >= amplitudeResult[i - 1, j + 1]) &&
(i == imageSizeY - 1 || j == 0 || amplitudeResult[i, j] > amplitudeResult[i + 1, j - 1]))
{
nmsResult[i, j] = amplitudeResult[i, j];
}
}
else
{
if (angle == 3 || angle == 7)
{
if ((i == 0 || j == 0 || amplitudeResult[i, j] >= amplitudeResult[i - 1, j - 1]) &&
(i == imageSizeY - 1 || j == imageSizeX - 1 || amplitudeResult[i, j] > amplitudeResult[i + 1, j + 1]))
{
nmsResult[i, j] = amplitudeResult[i, j];
}
}
else
{
if ((j == 0 || amplitudeResult[i, j] >= amplitudeResult[i, j - 1]) &&
(j == imageSizeX - 1 || amplitudeResult[i, j] > amplitudeResult[i, j + 1]))
{
nmsResult[i, j] = amplitudeResult[i, j];
}
}
}
}
}
}
float[,] hysteresisResult = new float[imageSizeY, imageSizeX];
bool[,] retainedPositions = applyHysteresisThreshold(nmsResult, imageSizeX, imageSizeY);
for (var i = 0; i < imageSizeY; i++)
{
for (var j = 0; j < imageSizeX; j++)
{
if (retainedPositions[i, j])
{
hysteresisResult[i, j] = nmsResult[i, j];
}
}
}
for (var i = 0; i < imageSizeY; i++)
{
for (var j = 0; j < imageSizeX; j++)
{
if (hysteresisResult[i, j] < 255)
{
outputGray[i, j] = (byte)(hysteresisResult[i, j] + 0.5f);
}
else
{
outputGray[i, j] = 255;
}
}
}
}
ImageDescription outputImage = new ImageDescription();
outputImage.sizeX = imageSizeX;
outputImage.sizeY = imageSizeY;
foreach (ColorChannelEnum colorChannel in Enum.GetValues(typeof(ColorChannelEnum)))
{
outputImage.setColorChannel(colorChannel, inputImage.getColorChannel(colorChannel));
}
outputImage.setColorChannel(ColorChannelEnum.Kirsch, outputGray);
return(outputImage);
}
public virtual ImageDescription filter(ImageDescription inputImage)
{
inputImage.computeGrayscale();
int imageSizeX = inputImage.sizeX;
int imageSizeY = inputImage.sizeY;
byte[,] inputGray = inputImage.gray;
byte[,] outputGray = new byte[imageSizeY, imageSizeX];
// 1. Gauss
float[,] gaussConvolutionMatrix = FilterBankUtil.generateNormalizedGaussConvolutionMatrix(sigma, 5);
float[,] gaussResult = ImageDescriptionUtil.mirroredMarginConvolution(inputGray, gaussConvolutionMatrix);
// 2. Gradient
float[,] dx = ImageDescriptionUtil.mirroredMarginConvolution(gaussResult, FilterBankUtil.normalizedSobelX);
float[,] dy = ImageDescriptionUtil.mirroredMarginConvolution(gaussResult, FilterBankUtil.normalizedSobelY);
// 3. Gradient Amplitude
float[,] amplitudeResult = new float[imageSizeY, imageSizeX];
for (int i = 0; i < imageSizeY; i++)
{
for (int j = 0; j < imageSizeX; j++)
{
amplitudeResult[i, j] = (float)Math.Sqrt(dx[i, j] * dx[i, j] + dy[i, j] * dy[i, j]);
}
}
// 4. Angle of gradient
float[,] anglesResult = new float[imageSizeY, imageSizeX];
for (int i = 0; i < imageSizeY; i++)
{
for (int j = 0; j < imageSizeX; j++)
{
anglesResult[i, j] = (float)Math.Atan2(dx[i, j], dy[i, j]);
}
}
// 5. Non maximal suppresion
float[,] nmsResult = new float[imageSizeY, imageSizeX];
for (int i = 1; i < imageSizeY - 1; i++)
{
for (int j = 1; j < imageSizeX - 1; j++)
{
float angle = anglesResult[i, j];
if ((angle <= (5 * Math.PI) / 8 && angle > (3 * Math.PI) / 8) || (angle > -(5 * Math.PI) / 8 && angle <= -(3 * Math.PI) / 8))
{
if (amplitudeResult[i, j] > amplitudeResult[i - 1, j] && amplitudeResult[i, j] > amplitudeResult[i + 1, j])
{
nmsResult[i, j] = amplitudeResult[i, j];
}
}
else
{
if (angle <= (3 * Math.PI) / 8 && angle > Math.PI / 8 || angle > -(7 * Math.PI) / 8 && angle <= -(5 * Math.PI) / 8)
{
if (amplitudeResult[i, j] > amplitudeResult[i - 1, j + 1] && amplitudeResult[i, j] > amplitudeResult[i + 1, j - 1])
{
nmsResult[i, j] = amplitudeResult[i, j];
}
}
else
{
if (angle <= (7 * Math.PI / 8) && angle > (5 * Math.PI / 8) || angle > -(3 * Math.PI) / 8 && angle < -(Math.PI / 8))
{
if (amplitudeResult[i, j] > amplitudeResult[i - 1, j - 1] && amplitudeResult[i, j] > amplitudeResult[i + 1, j + 1])
{
nmsResult[i, j] = amplitudeResult[i, j];
}
}
else
{
if (amplitudeResult[i, j] > amplitudeResult[i, j - 1] && amplitudeResult[i, j] > amplitudeResult[i, j + 1])
{
nmsResult[i, j] = amplitudeResult[i, j];
}
}
}
}
}
}
// 6. Hysteresis thresolding
float[,] hysteresisResult = new float[imageSizeY, imageSizeX];
bool[,] retainedPositions = applyHysteresisThreshold(nmsResult, imageSizeX, imageSizeY);
for (var i = 0; i < imageSizeY; i++)
{
for (var j = 0; j < imageSizeX; j++)
{
if (retainedPositions[i, j])
{
hysteresisResult[i, j] = nmsResult[i, j];
}
}
}
for (var i = 0; i < imageSizeY; i++)
{
for (var j = 0; j < imageSizeX; j++)
{
if (hysteresisResult[i, j] < 255)
{
outputGray[i, j] = (byte)(hysteresisResult[i, j] + 0.5f);
}
else
{
outputGray[i, j] = 255;
}
}
}
ImageDescription outputImage = new ImageDescription();
outputImage.sizeX = imageSizeX;
outputImage.sizeY = imageSizeY;
foreach (ColorChannelEnum colorChannel in Enum.GetValues(typeof(ColorChannelEnum)))
{
outputImage.setColorChannel(colorChannel, inputImage.getColorChannel(colorChannel));
}
outputImage.setColorChannel(ColorChannelEnum.Canny, outputGray);
return(outputImage);
}