public Bitmap Resample(Bitmap image, int width, int height)
{
ResamplingService resamplingService = new ResamplingService();
resamplingService.Filter = ResamplingFilters.Lanczos3;
ushort[][,] input = ResamplingFilter.ConvertBitmapToArray((Bitmap)image);
ushort[][,] output = resamplingService.Resample(input, width, height);
Bitmap result = (Bitmap)ResamplingFilter.ConvertArrayToBitmap(output);
return(result);
}
public void Resample(ResamplingFilters filter, int newWidth, int newHeight)
{
if (Disposed)
{
return;
}
ResamplingService resamplingService = new ResamplingService();
resamplingService.Filter = filter;
var array = ResamplingFilter.ConvertByteArrayToArray((byte *)this.Bytes.ToPointer(), this.Width, this.Height);
var result = resamplingService.Resample(array, newWidth, newHeight);
this.InternalResize(newWidth, newHeight);
ResamplingFilter.ConvertArrayToByteArray(result, (byte *)this.Bytes.ToPointer());
}
/// <summary>
/// Resamples input array to a new array using current resampling filter.
/// </summary>
/// <param name="input">Input array.</param>
/// <param name="nWidth">Width of the output array.</param>
/// <param name="nHeight">Height of the output array.</param>
/// <returns>Output array.</returns>
public ushort[][,] Resample(ushort[][,] input, int nWidth, int nHeight)
{
if (input == null || input.Length == 0 || nWidth < 1 || nHeight < 1)
{
return(null);
}
ResamplingFilter filter = ResamplingFilter.Create(this.filter);
int width = input[0].GetLength(0);
int height = input[0].GetLength(1);
int planes = input.Length;
this.covered = 0;
this.total = (nWidth + height);
// create bitmaps
ushort[][,] work = new ushort[planes][, ];
ushort[][,] output = new ushort[planes][, ];
int c = 0;
for (c = 0; c < planes; c++)
{
work[c] = new ushort[nWidth, height];
output[c] = new ushort[nWidth, nHeight];
}
double xScale = ((double)nWidth / width);
double yScale = ((double)nHeight / height);
ContributorEntry[] contrib = new ContributorEntry[nWidth];
double wdth = 0, center = 0, weight = 0, intensity = 0;
int left = 0, right = 0, i = 0, j = 0, k = 0;
// horizontal downsampling
if (xScale < 1.0)
{
// scales from bigger to smaller width
wdth = (filter.defaultFilterRadius / xScale);
for (i = 0; i < nWidth; i++)
{
contrib[i].n = 0;
contrib[i].p = new Contributor[(int)Math.Floor(2 * wdth + 1)];
contrib[i].wsum = 0;
center = ((i + 0.5) / xScale);
left = (int)(center - wdth);
right = (int)(center + wdth);
for (j = left; j <= right; j++)
{
weight = filter.GetValue((center - j - 0.5) * xScale);
if ((weight == 0) || (j < 0) || (j >= width))
{
continue;
}
contrib[i].p[contrib[i].n].pixel = j;
contrib[i].p[contrib[i].n].weight = weight;
contrib[i].wsum += weight;
contrib[i].n++;
}
if (aborting)
{
goto End;
}
}
}
else
{
// horizontal upsampling
// scales from smaller to bigger width
for (i = 0; i < nWidth; i++)
{
contrib[i].n = 0;
contrib[i].p = new Contributor[(int)Math.Floor(2 * filter.defaultFilterRadius + 1)];
contrib[i].wsum = 0;
center = ((i + 0.5) / xScale);
left = (int)Math.Floor(center - filter.defaultFilterRadius);
right = (int)Math.Ceiling(center + filter.defaultFilterRadius);
for (j = left; j <= right; j++)
{
weight = filter.GetValue(center - j - 0.5);
if ((weight == 0) || (j < 0) || (j >= width))
{
continue;
}
contrib[i].p[contrib[i].n].pixel = j;
contrib[i].p[contrib[i].n].weight = weight;
contrib[i].wsum += weight;
contrib[i].n++;
}
if (aborting)
{
goto End;
}
}
}
// filter horizontally from input to work
for (c = 0; c < planes; c++)
{
for (k = 0; k < height; k++)
{
for (i = 0; i < nWidth; i++)
{
intensity = 0;
for (j = 0; j < contrib[i].n; j++)
{
weight = contrib[i].p[j].weight;
if (weight == 0)
{
continue;
}
intensity += (input[c][contrib[i].p[j].pixel, k] * weight);
}
work[c][i, k] = (ushort)Math.Min(Math.Max(intensity / contrib[i].wsum + 0.5, UInt16.MinValue), UInt16.MaxValue);
}
if (aborting)
{
goto End;
}
this.covered++;
}
}
// pre-calculate filter contributions for a column
contrib = new ContributorEntry[nHeight];
// vertical downsampling
if (yScale < 1.0)
{
// scales from bigger to smaller height
wdth = (filter.defaultFilterRadius / yScale);
for (i = 0; i < nHeight; i++)
{
contrib[i].n = 0;
contrib[i].p = new Contributor[(int)Math.Floor(2 * wdth + 1)];
contrib[i].wsum = 0;
center = ((i + 0.5) / yScale);
left = (int)(center - wdth);
right = (int)(center + wdth);
for (j = left; j <= right; j++)
{
weight = filter.GetValue((center - j - 0.5) * yScale);
if ((weight == 0) || (j < 0) || (j >= height))
{
continue;
}
contrib[i].p[contrib[i].n].pixel = j;
contrib[i].p[contrib[i].n].weight = weight;
contrib[i].wsum += weight;
contrib[i].n++;
}
if (aborting)
{
goto End;
}
}
}
else
{
// vertical upsampling
// scales from smaller to bigger height
for (i = 0; i < nHeight; i++)
{
contrib[i].n = 0;
contrib[i].p = new Contributor[(int)Math.Floor(2 * filter.defaultFilterRadius + 1)];
contrib[i].wsum = 0;
center = ((i + 0.5) / yScale);
left = (int)(center - filter.defaultFilterRadius);
right = (int)(center + filter.defaultFilterRadius);
for (j = left; j <= right; j++)
{
weight = filter.GetValue(center - j - 0.5);
if ((weight == 0) || (j < 0) || (j >= height))
{
continue;
}
contrib[i].p[contrib[i].n].pixel = j;
contrib[i].p[contrib[i].n].weight = weight;
contrib[i].wsum += weight;
contrib[i].n++;
}
if (aborting)
{
goto End;
}
}
}
// filter vertically from work to output
for (c = 0; c < planes; c++)
{
for (k = 0; k < nWidth; k++)
{
for (i = 0; i < nHeight; i++)
{
intensity = 0;
for (j = 0; j < contrib[i].n; j++)
{
weight = contrib[i].p[j].weight;
if (weight == 0)
{
continue;
}
intensity += (work[c][k, contrib[i].p[j].pixel] * weight);
}
output[c][k, i] = (ushort)Math.Min(Math.Max(intensity / contrib[i].wsum + 0.5, UInt16.MinValue), UInt16.MaxValue);
}
if (aborting)
{
goto End;
}
this.covered++;
}
}
End :;
work = null;
return(output);
}
public static ResamplingFilter Create(ResamplingFilters filter)
{
ResamplingFilter resamplingFilter = null;
switch (filter)
{
case ResamplingFilters.Box:
resamplingFilter = new BoxFilter();
break;
case ResamplingFilters.Triangle:
resamplingFilter = new TriangleFilter();
break;
case ResamplingFilters.Hermite:
resamplingFilter = new HermiteFilter();
break;
case ResamplingFilters.Bell:
resamplingFilter = new BellFilter();
break;
case ResamplingFilters.CubicBSpline:
resamplingFilter = new CubicBSplineFilter();
break;
case ResamplingFilters.Lanczos3:
resamplingFilter = new Lanczos3Filter();
break;
case ResamplingFilters.Mitchell:
resamplingFilter = new MitchellFilter();
break;
case ResamplingFilters.Cosine:
resamplingFilter = new CosineFilter();
break;
case ResamplingFilters.CatmullRom:
resamplingFilter = new CatmullRomFilter();
break;
case ResamplingFilters.Quadratic:
resamplingFilter = new QuadraticFilter();
break;
case ResamplingFilters.QuadraticBSpline:
resamplingFilter = new QuadraticBSplineFilter();
break;
case ResamplingFilters.CubicConvolution:
resamplingFilter = new CubicConvolutionFilter();
break;
case ResamplingFilters.Lanczos8:
resamplingFilter = new Lanczos8Filter();
break;
}
return(resamplingFilter);
}
