/// <summary>
/// Any pixel values below threshold will be changed to 0.
/// Any pixel values above (or equal to) threshold will be changed to 1.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to process</param>
/// <param name="threshold">Binary threshold</param>
/// <returns>New image as binary</returns>
public static T AsImage <T>(T image, byte threshold) where T : Image
{
Bitmap binaryBitmap = AsBitmap(image, threshold);
// Convert to original format
return((T)ImageFormatting.ToFormat(binaryBitmap, image.RawFormat));
}
/// <summary>
/// Applies localized/adaptive region thresholding to image using Chow & Kaneko method.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to process</param>
/// <param name="horizontalRegions">Number of horizonal regions to apply</param>
/// <param name="verticalRegions">Number of veritical regions to apply</param>
/// <returns>New image with localized threshold applied</returns>
public static T ApplyChowKanekoMethod <T>(T image, int horizontalRegions, int verticalRegions) where T : Image
{
Bitmap bitmap = ImageFormatting.ToBitmap(image);
ApplyChowKanekoMethodDirect(ref bitmap, horizontalRegions, verticalRegions);
return((T)ImageFormatting.Convert(bitmap, image.RawFormat));
}
/// <summary>
/// Any pixel values outside the threshold will be changed to min/max.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to process</param>
/// <param name="minValue">Minimum threshold value</param>
/// <param name="maxValue">Maximum threshold value</param>
/// <returns>New image with threshold applied</returns>
public static T ApplyMinMax <T>(T image, byte minValue, byte maxValue) where T : Image
{
Bitmap bitmap = ImageFormatting.ToBitmap(image);
ApplyMinMaxDirect(ref bitmap, minValue, maxValue);
return((T)ImageFormatting.Convert(bitmap, image.RawFormat));
}
/// <summary>
/// Applies thresholding to image using Otsu's Method.
/// Returned image will consist of black (0) and white (255) values only.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to process</param>
/// <returns>New image with threshold applied</returns>
public static T ApplyOtsuMethod <T>(T image) where T : Image
{
Bitmap bitmap = ImageFormatting.ToBitmap(image);
ApplyOtsuMethodDirect(ref bitmap);
return((T)ImageFormatting.Convert(bitmap, image.RawFormat));
}
/// <summary>
/// Any pixel values below threshold will be changed to 0 (black).
/// Any pixel values above (or equal to) threshold will be changed to 255 (white).
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to process</param>
/// <param name="threshold">Threshold value</param>
/// <returns>New image with threshold applied</returns>
public static T Apply <T>(T image, byte threshold) where T : Image
{
Bitmap bitmap = ImageFormatting.ToBitmap(image);
ApplyDirect(ref bitmap, threshold);
return((T)ImageFormatting.Convert(bitmap, image.RawFormat));
}
/// <summary>
/// Histogram Equalization will enhance general contrast
/// by distributing grey levels wider and more evenly.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to equalize</param>
/// <returns>Equalized image</returns>
public static T HistogramEqualization <T>(T image) where T : Image
{
Bitmap bitmap = ImageFormatting.ToBitmap(image);
HistogramEqualizationDirect(ref bitmap);
return((T)ImageFormatting.Convert(bitmap, image.RawFormat));
}
/// <summary>
/// Stretches image contrast to specified min/max values.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to process</param>
/// <param name="min">Minimum contrast value</param>
/// <param name="max">Maximum contrast value</param>
/// <returns>Contrast-stretched image</returns>
public static T Stretch <T>(T image, byte min, byte max) where T : Image
{
Bitmap bitmap = ImageFormatting.ToBitmap(image);
StretchDirect(ref bitmap, min, max);
return((T)ImageFormatting.Convert(bitmap, image.RawFormat));
}
/// <summary>
/// Inverts image to negative.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to convert</param>
/// <returns>Negative image</returns>
public static T ToNegative <T>(T image) where T : Image
{
Bitmap bitmap = ImageFormatting.ToBitmap(image);
ToNegativeDirect(ref bitmap);
return((T)ImageFormatting.Convert(bitmap, image.RawFormat));
}
/// <summary>
/// Applies color filter to image.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to process</param>
/// <param name="r">Red component to apply</param>
/// <param name="g">Green component to apply</param>
/// <param name="b">Blue component to apply</param>
/// <returns>New image with filter applied</returns>
public static T ApplyFilterRGB <T>(T image, byte r, byte g, byte b) where T : Image
{
Bitmap bitmap = ImageFormatting.ToBitmap(image);
ApplyFilterDirectRGB(ref bitmap, r, g, b);
return((T)ImageFormatting.Convert(bitmap, image.RawFormat));
}
/// <summary>
/// Converts the image to a bitmap, and gets the bytes.
/// </summary>
/// <param name="image">Image to get bytes from</param>
/// <param name="bitmapData">Data relating to bitmap</param>
/// <returns>Image bytes (without header info)</returns>
public static byte[] FromImage(Image image, out BitmapData bitmapData)
{
if (image is Bitmap bmp)
{
return(GetBitmapBytes(bmp, out bitmapData));
}
else
{
using (Bitmap bitmap = ImageFormatting.ToBitmap(image))
{
return(GetBitmapBytes(bitmap, out bitmapData));
}
}
}
/// <summary>
/// Get the average pixel value between min and max.
/// </summary>
/// <param name="image">Image to process</param>
/// <param name="min">Minimum byte value</param>
/// <param name="max">Maximum byte value</param>
/// <returns>Average pixel intensity</returns>
public static byte GetAverageValue(Image image, byte min, byte max)
{
if (image is Bitmap bmp)
{
return(GetAverageBitmapValue(bmp, min, max));
}
else
{
using (Bitmap bitmap = ImageFormatting.ToBitmap(image))
{
return(GetAverageBitmapValue(bitmap, min, max));
}
}
}
/// <summary>
/// Gets the minimum & maximum pixel value within an image.
/// For color images, min/max pixel avg is returned.
/// </summary>
/// <param name="image">Image to search</param>
/// <param name="findMin">Determines whether to return min value</param>
/// <param name="findMax">Determines whether to return max value</param>
/// <returns>min, max bytes</returns>
private static Tuple <byte, byte> GetMinMaxValue(Image image, bool findMin, bool findMax)
{
if (image is Bitmap bmp)
{
return(GetMinMaxBitmapValue(bmp, findMin, findMax));
}
else
{
using (Bitmap bitmap = ImageFormatting.ToBitmap(image))
{
return(GetMinMaxBitmapValue(bitmap, findMin, findMax));
}
}
}
/// <summary>
/// Applies multiple convolution kernels to source image, then combines the results.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to apply kernel to</param>
/// <param name="convolutionTypes">Convolutions to apply</param>
/// <returns>Image with all kernels combined</returns>
public static T ApplyKernelsThenCombine <T>(T image, params ConvolutionType[] convolutionTypes) where T : Image
{
if (image is Bitmap bmp)
{
return((T)(Image)ApplyKernelsThenCombine(bmp, convolutionTypes));
}
else
{
// Convert to bitmap for image processing
using (Bitmap bitmap = ImageFormatting.ToBitmap(image))
{
using (Bitmap combinedBitmap = ApplyKernelsThenCombine(bitmap, convolutionTypes))
{
// Return processed image to original format
return((T)ImageFormatting.ToFormat(combinedBitmap, image.RawFormat));
}
}
}
}
/// <summary>
/// Applies convolution matrix/kernel to image.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to apply kernel to</param>
/// <param name="kernelMatrix">Kernel matrix</param>
/// <returns>Image with kernel applied</returns>
public static T ApplyKernel <T>(T image, int[,] kernelMatrix) where T : Image
{
// Skip conversion
if (image is Bitmap bmp)
{
return((T)(Image)ApplyKernel(bmp, kernelMatrix));
}
else
{
// Convert to bitmap for image processing
using (Bitmap bitmap = ImageFormatting.ToBitmap(image))
{
// Apply filter to bitmap
using (Bitmap bitmapWithFilter = ApplyKernel(bitmap, kernelMatrix))
{
// Covert processed image to original format
return((T)ImageFormatting.ToFormat(bitmapWithFilter, image.RawFormat));
}
}
}
}
/// <summary>
/// Crops an image based on the crop region.
/// </summary>
/// <typeparam name="T">Image type to process and return</typeparam>
/// <param name="image">Image to crop</param>
/// <param name="cropRegion">Region within image to crop</param>
/// <returns>Cropped image</returns>
public static T ByRegion <T>(T image, Rectangle cropRegion) where T : Image
{
// Check if already a bitmap
if (image is Bitmap bmp)
{
return((T)(Image)CropBitmap(bmp, cropRegion));
}
else
{
// Convert to bitmap
using (Bitmap bitmap = ImageFormatting.ToBitmap(image))
{
// Crop as bitmap
using (Image croppedBitmap = CropBitmap(bitmap, cropRegion))
{
// Restore original image format
return((T)ImageFormatting.ToFormat(croppedBitmap, image.RawFormat));
}
}
}
}
/// <summary>
/// Combines multiple images together.
/// (Pixel values combined via bitwise or, not averaged)
/// </summary>
/// <param name="images">Images to combine</param>
/// <returns>New combined image as bitmap</returns>
public static Bitmap All<T>(IEnumerable<T> images) where T : Image
{
// Check have at least 1 image
if (!images.Any())
{
return null;
}
// Use first image as starting point
Bitmap combinedImage = ImageFormatting.ToBitmap(images.ElementAt(0));
// Get bytes for image
byte[] rgbValues1 = ImageEdit.Begin(combinedImage, out BitmapData bmpData1);
try
{
// Get image 1 data
int pixelDepth1 = bmpData1.GetPixelDepth();
int pixelDepthWithoutAlpha = Math.Min(pixelDepth1, Constants.PixelDepthRGB);
int stride1 = bmpData1.Stride;
int width1 = bmpData1.GetStrideWithoutPadding();
int height1 = bmpData1.Height;
// Add additional images to first
foreach (Image image in images.Skip(1))
{
// Only reading this image
byte[] rgbValues2 = ImageBytes.FromImage(image, out BitmapData bmpData2);
// Check both images are color or B&W
if (pixelDepth1 == bmpData2.GetPixelDepth())
{
// Protect against different sized images
int limit = Math.Min(bmpData1.GetSafeArrayLimitForImage(rgbValues1), bmpData2.GetSafeArrayLimitForImage(rgbValues2));
int minHeight = Math.Min(height1, bmpData2.Height);
int minStride = Math.Min(stride1, bmpData2.Stride);
int minWidth = Math.Min(width1, bmpData2.GetStrideWithoutPadding());
for (int y = 0; y < minHeight; y++)
{
// Images may have extra bytes per row to pad for CPU addressing.
// so need to ensure we traverse to the correct byte when moving between rows.
int offset = y * minStride;
for (int x = 0; x < minWidth; x += pixelDepth1)
{
int i = offset + x;
if (i < limit)
{
for (int j = 0; j < pixelDepthWithoutAlpha; j++)
{
// Combine images
rgbValues1[i + j] |= rgbValues2[i + j];
}
}
else
{
break;
}
}
}
}
else
{
throw new ArgumentException("Not all images have the same color depth");
}
}
}
finally
{
// Release combined image
ImageEdit.End(combinedImage, bmpData1, rgbValues1);
}
return combinedImage;
}