TKernelResampler

Ancestors

TPersistent

Description

TKernelResampler is a general class for image resampling using arbitrary convolution filters. It implements a fast method for resizing images, by precomputing kernel weights in mapping tables or coefficient bins.

For single-sample look-ups, the GetSample method supports three different kernel modes:

kmDynamic — kernel weights are computed on-the-fly;
kmTableNearest — kernel weights are stored in a table, nearest-neighbor is used for the look-up;
kmTableLinear — same as above, but uses linear interpolation for the look-up.

For further information, see topic about Sampling and Rasterization.

Reference

Methods Properties Events

In TKernelResampler:

Create Kernel

Destroy KernelClassName

FinalizeSampling KernelMode

GetSample TableSize

PrepareSampling

In TBitmap32Resampler:

Changed Bitmap

GetSampleBounds PixelAccessMode

HasBounds TransformerClass

In TCustomResampler:

Resample Width

In TNotifiablePersistent:

BeginUpdate UpdateCount OnChange

EndUpdate

Methods	Properties	Events
In TKernelResampler:
Create	Kernel
Destroy	KernelClassName
FinalizeSampling	KernelMode
GetSample	TableSize
PrepareSampling
In TBitmap32Resampler:
Changed	Bitmap
GetSampleBounds	PixelAccessMode
HasBounds	TransformerClass
In TCustomResampler:
Resample	Width
In TNotifiablePersistent:
BeginUpdate	UpdateCount	OnChange
EndUpdate

TKernelResampler

Ancestors

Description

Reference

See Also