/// <summary>
/// <para>(Accord .NET internal call)</para>
/// In image processing, a Gabor filter, named after Dennis Gabor, is a linear
/// filter used for edge detection. Frequency and orientation representations
/// of Gabor filters are similar to those of the human visual system, and they
/// have been found to be particularly appropriate for texture representation
/// and discrimination. In the spatial domain, a 2D Gabor filter is a Gaussian
/// kernel function modulated by a sinusoidal plane wave. The Gabor filters are
/// self-similar: all filters can be generated from one mother wavelet by dilation
/// and rotation.
/// </summary>
/// <param name="img">Image.</param>
/// <param name="gaborFilter">Gabor filter instance.
/// <para>To avoid calculating Gabor every time use this function overload that receives instance.</para>
/// </param>
/// <returns>Filtered image.</returns>
internal static Gray <byte>[,] GaborFilter(this Gray <byte>[,] img, GaborFilter gaborFilter)
{
return(img.ApplyFilter(gaborFilter));
}
/// <summary>
/// Applies wavelet transform filter (Accord.NET).
/// </summary>
/// <param name="img">Image.</param>
/// <param name="wavelet">A wavelet function.</param>
/// <param name="backward">True to perform backward transform, false otherwise.</param>
/// <returns>Transformed image.</returns>
public static Gray <byte>[,] WaveletTransform(this Gray <byte>[,] img, IWavelet wavelet, bool backward = false)
{
WaveletTransform wt = new WaveletTransform(wavelet, backward);
return(img.ApplyFilter((BaseFilter)wt));
}
/// <summary>
/// <para>(Accord .NET internal call)</para>
/// The Variance filter replaces each pixel in an image by its
/// neighborhood variance. The end result can be regarded as an
/// border enhancement, making the Variance filter suitable to
/// be used as an edge detection mechanism.
/// </summary>
/// <param name="img">Image.</param>
/// <param name="radius">The radius neighborhood used to compute a pixel's local variance.</param>
/// <returns>Processed image.</returns>
public static Gray <byte>[,] Variance(this Gray <byte>[,] img, int radius = 2)
{
Variance v = new Variance(radius);
return(img.ApplyFilter(v));
}
/// <summary>
/// Kuwahara filter.
/// <para>Accord.NET internal call. See: <see cref="Accord.Imaging.Filters.Kuwahara"/> for details.</para>
/// </summary>
/// <param name="img">Image.</param>
/// <param name="size">the size of the kernel used in the Kuwahara filter. This should be odd and greater than or equal to five</param>
/// <param name="blockSize">the size of each of the four inner blocks used in the Kuwahara filter. This is always half the <paramref name="size"/> minus one.</param>
/// <param name="inPlace">Apply in place or not. If it is set to true return value can be omitted.</param>
/// <returns>Processed image.</returns>
public static Gray <byte>[,] Kuwahara(this Gray <byte>[,] img, int size = 5, int blockSize = 2, bool inPlace = false)
{
Kuwahara k = new Kuwahara();
return(img.ApplyFilter(k, inPlace));
}
