private static void _ScaleScan(float[] dest, int destOrigin, int destStride, int destWidth, float[] src, int srcOrigin, int srcStride, ScaleScanFilter filter)
{
Contract.Requires(dest != null);
Contract.Requires(src != null);
var coeffIndex = 0;
var destIndex = 0;
for (var x = 0; x < destWidth; x++)
{
var srcIndex = filter.Pos[x] * srcStride;
var sum = 0f;
for (var k = 0; k < filter.Width; k++, srcIndex += srcStride)
{
sum += filter.Coeff[coeffIndex + k] * src[srcOrigin + srcIndex];
}
dest[destOrigin + destIndex] = sum;
destIndex += destStride;
coeffIndex += filter.Width;
}
}
private static void _ScaleScan(float[] dest, int destOrigin, int destStride, int destWidth, float[] src, int srcOrigin, int srcStride, ScaleScanFilter filter) {
Contract.Requires(dest != null);
Contract.Requires(src != null);
var coeffIndex = 0;
var destIndex = 0;
for (var x = 0; x < destWidth; x++) {
var srcIndex = filter.Pos[x] * srcStride;
var sum = 0f;
for (var k = 0; k < filter.Width; k++, srcIndex += srcStride)
sum += filter.Coeff[coeffIndex + k] * src[srcOrigin + srcIndex];
dest[destOrigin + destIndex] = sum;
destIndex += destStride;
coeffIndex += filter.Width;
}
}
/// <summary>
/// Create scanline interpolation filter to be applied with ScaleScan
/// This routine creates a scalescanfilter for 1-D interpolation of samples at
/// the locations
/// XStart + n*XStep, n = 0, ..., DestWidth - 1,
/// where the pixels of the source are logically located at the integers. Half-
/// sample even symmetric extension is used to handle the boundaries.
/// </summary>
/// <param name="destWidth">width after interpolation</param>
/// <param name="xstart">leftmost sampling location (in input coordinates)</param>
/// <param name="xstep">the length between successive samples (in input coordinates)</param>
/// <param name="srcWidth">width of the input</param>
/// <param name="kernel">interpolation kernel function to use</param>
/// <param name="kernelRadius">kernel support radius</param>
/// <param name="kernelNormalize">if set to <c>true</c> filter rows are normalized to sum to 1</param>
/// <param name="boundary">boundary handling</param>
/// <returns></returns>
///
///
private static ScaleScanFilter _MakeScaleScanFilter(int destWidth, float xstart, float xstep, int srcWidth, Kernels.FixedRadiusKernelMethod kernel, float kernelRadius, bool kernelNormalize, OutOfBoundsUtils.OutOfBoundsHandler boundary)
{
Contract.Requires(kernel != null);
var kernelWidth = (int)Math.Ceiling(2 * kernelRadius);
var filterWidth = (srcWidth < kernelWidth) ? srcWidth : kernelWidth;
var filterCoeff = new float[filterWidth * destWidth];
var filterPos = new short[destWidth];
var result = new ScaleScanFilter {
Coeff = filterCoeff,
Pos = filterPos,
Width = filterWidth
};
var maxPos = srcWidth - filterWidth;
var coeffIndex = 0;
for (var destX = 0; destX < destWidth; destX++)
{
var srcX = xstart + xstep * destX;
var pos = (int)Math.Ceiling(srcX - kernelRadius);
if (pos < 0 || maxPos < pos)
{
filterPos[destX] = (short)(pos <0 ? 0 : pos> maxPos ? maxPos : pos);
for (var n = 0; n < filterWidth; n++)
{
filterCoeff[coeffIndex + n] = 0;
}
for (var n = 0; n < kernelWidth; n++)
{
var index = pos + n;
if (index < 0 || index >= srcWidth)
{
index = boundary(index, srcWidth, index < 0);
}
filterCoeff[coeffIndex + index - filterPos[destX]]
+= (float)kernel(srcX - index);
}
}
else
{
filterPos[destX] = (short)pos;
for (var n = 0; n < filterWidth; n++)
{
filterCoeff[coeffIndex + n] = (float)kernel(srcX - (pos + n));
}
}
if (kernelNormalize) /* Normalize */
{
var sum = 0f;
for (var n = 0; n < filterWidth; n++)
{
sum += filterCoeff[coeffIndex + n];
}
for (var n = 0; n < filterWidth; n++)
{
filterCoeff[coeffIndex + n] /= sum;
}
}
coeffIndex += filterWidth;
}
return(result);
}
/// <summary>
/// Create scanline interpolation filter to be applied with ScaleScan
/// This routine creates a scalescanfilter for 1-D interpolation of samples at
/// the locations
/// XStart + n*XStep, n = 0, ..., DestWidth - 1,
/// where the pixels of the source are logically located at the integers. Half-
/// sample even symmetric extension is used to handle the boundaries.
/// </summary>
/// <param name="destWidth">width after interpolation</param>
/// <param name="xstart">leftmost sampling location (in input coordinates)</param>
/// <param name="xstep">the length between successive samples (in input coordinates)</param>
/// <param name="srcWidth">width of the input</param>
/// <param name="kernel">interpolation kernel function to use</param>
/// <param name="kernelRadius">kernel support radius</param>
/// <param name="kernelNormalize">if set to <c>true</c> filter rows are normalized to sum to 1</param>
/// <param name="boundary">boundary handling</param>
/// <returns></returns>
///
///
private static ScaleScanFilter _MakeScaleScanFilter(int destWidth, float xstart, float xstep, int srcWidth, Kernels.FixedRadiusKernelMethod kernel, float kernelRadius, bool kernelNormalize, OutOfBoundsUtils.OutOfBoundsHandler boundary) {
Contract.Requires(kernel != null);
var kernelWidth = (int)Math.Ceiling(2 * kernelRadius);
var filterWidth = (srcWidth < kernelWidth) ? srcWidth : kernelWidth;
var filterCoeff = new float[filterWidth * destWidth];
var filterPos = new short[destWidth];
var result = new ScaleScanFilter {
Coeff = filterCoeff,
Pos = filterPos,
Width = filterWidth
};
var maxPos = srcWidth - filterWidth;
var coeffIndex = 0;
for (var destX = 0; destX < destWidth; destX++) {
var srcX = xstart + xstep * destX;
var pos = (int)Math.Ceiling(srcX - kernelRadius);
if (pos < 0 || maxPos < pos) {
filterPos[destX] = (short)(pos < 0 ? 0 : pos > maxPos ? maxPos : pos);
for (var n = 0; n < filterWidth; n++)
filterCoeff[coeffIndex + n] = 0;
for (var n = 0; n < kernelWidth; n++) {
var index = pos + n;
if (index < 0 || index >= srcWidth)
index = boundary(index, srcWidth,index<0);
filterCoeff[coeffIndex + index - filterPos[destX]]
+= (float) kernel(srcX - index);
}
} else {
filterPos[destX] = (short)pos;
for (var n = 0; n < filterWidth; n++)
filterCoeff[coeffIndex + n] = (float)kernel(srcX - (pos + n));
}
if (kernelNormalize) /* Normalize */ {
var sum = 0f;
for (var n = 0; n < filterWidth; n++)
sum += filterCoeff[coeffIndex + n];
for (var n = 0; n < filterWidth; n++)
filterCoeff[coeffIndex + n] /= sum;
}
coeffIndex += filterWidth;
}
return (result);
}
