/// <summary>
/// Computes the weights to apply at each pixel when resizing.
/// </summary>
/// <param name="sampler">The <see cref="IResampler"/></param>
/// <param name="destinationSize">The destination size</param>
/// <param name="sourceSize">The source size</param>
/// <param name="memoryAllocator">The <see cref="MemoryAllocator"/> to use for buffer allocations</param>
/// <returns>The <see cref="ResizeKernelMap"/></returns>
public static ResizeKernelMap Calculate(
IResampler sampler,
int destinationSize,
int sourceSize,
MemoryAllocator memoryAllocator)
{
double ratio = (double)sourceSize / destinationSize;
double scale = ratio;
if (scale < 1)
{
scale = 1;
}
int radius = (int)TolerantMath.Ceiling(scale * sampler.Radius);
// 'ratio' is a rational number.
// Multiplying it by LCM(sourceSize, destSize)/sourceSize will result in a whole number "again".
// This value is determining the length of the periods in repeating kernel map rows.
int period = ImageMaths.LeastCommonMultiple(sourceSize, destinationSize) / sourceSize;
// the center position at i == 0:
double center0 = (ratio - 1) * 0.5;
double firstNonNegativeLeftVal = (radius - center0 - 1) / ratio;
// The number of rows building a "stairway" at the top and the bottom of the kernel map
// corresponding to the corners of the image.
// If we do not normalize the kernel values, these rows also fit the periodic logic,
// however, it's just simpler to calculate them separately.
int cornerInterval = (int)TolerantMath.Ceiling(firstNonNegativeLeftVal);
// If firstNonNegativeLeftVal was an integral value, we need firstNonNegativeLeftVal+1
// instead of Ceiling:
if (TolerantMath.AreEqual(firstNonNegativeLeftVal, cornerInterval))
{
cornerInterval++;
}
// If 'cornerInterval' is too big compared to 'period', we can't apply the periodic optimization.
// If we don't have at least 2 periods, we go with the basic implementation:
bool hasAtLeast2Periods = 2 * (cornerInterval + period) < destinationSize;
ResizeKernelMap result = hasAtLeast2Periods
? new PeriodicKernelMap(
memoryAllocator,
sampler,
sourceSize,
destinationSize,
ratio,
scale,
radius,
period,
cornerInterval)
: new ResizeKernelMap(
memoryAllocator,
sampler,
sourceSize,
destinationSize,
destinationSize,
ratio,
scale,
radius);
result.Initialize();
return(result);
}
public void LeastCommonMultiple(int a, int b, int expected)
{
int actual = ImageMaths.LeastCommonMultiple(a, b);
Assert.Equal(expected, actual);
}