Interface defining local to point image processing functionnalities. More...

#include <IImageLocalProcessing.h>

Inheritance diagram for eLynx::Image::IImageLocalProcessing:

Public Member Functions
virtual bool	Convolve (AbstractImage &ioImage, const Math::ConvolutionKerneld &iKernel, bool ibAbsolute, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Convolve with a kernel.
virtual bool	Convolve (AbstractImage &ioImage, const Math::ConvolutionKerneld &iKernel, double iThresholdMin, double iThresholdMax, bool ibAbsolute, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Convolve with a kernel on thresholded values.
virtual bool	Convolve (AbstractImage &ioImage, const Math::ConvolutionKerneld &iKernel1, const Math::ConvolutionKerneld &iKernel2, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Convolve with two separable kernels [Wx1] x [1xH].
virtual bool	ApplyBoxBlur (AbstractImage &ioImage, uint32 iWidth, uint32 iHeight, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Box blur filter, this is the blur filter with best performance with int64 kernel.
virtual bool	ApplySelectiveBlur (AbstractImage &ioImage, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Adaptive blur filter, this is a blur filter that protects edges.
virtual bool	ApplyGaussian (AbstractImage &ioImage, uint32 iWidth, uint32 iHeight, double iVariance, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Gaussian filter smooths the current image by convolving a Gaussian kernel(iWidth,iHeight) with the selected iVariance.
virtual bool	ApplyGaussian (AbstractImage &ioImage, double iRadius, double iVariance, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Gaussian filter smooths the current image by convolving a Gaussian kernel sized by iRadius and with the selected iVariance.
virtual bool	ApplyGaussian (AbstractImage &ioImage, double iRadius, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Gaussian filter smooths the current image by convolving a Gaussian kernel sized by iRadius and computed variance based of radius.
virtual bool	ApplyBilateral (AbstractImage &ioImage, double iRadius, double iVarianceSpatial, double iVarianceRange, EBorderFill iBorder, uint32 iIteration, uint32 iChannelMask, ProgressNotifier &iNotifier) const =0
	Apply bilateral filter to an image by means of a nonlinear combination of nearby image values.

Detailed Description

Interface defining local to point image processing functionnalities.

See Characteristics of Image Operations.

Convolution is a image processing technique that changes the intensities of a pixel to reflect the intensities of the surrounding pixels. Using convolution, you can get popular image effects like blur, sharpen, edge detection�effects, emboss ...

Member Function Documentation

virtual bool eLynx::Image::IImageLocalProcessing::ApplyBilateral	(	AbstractImage &	ioImage,
		double	iRadius,
		double	iVarianceSpatial,
		double	iVarianceRange,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Apply bilateral filter to an image by means of a nonlinear combination of nearby image values.

[1]	Bilateral Filtering for Gray and Color Images by C. Tomasi and R. Manduchi
[2]	Fast Bilateral Filtering for the Display of High-Dynamic-Range Images by Fr�do Durand and Julie Dorsey Laboratory for Computer Science, Massachusetts Institute of Technology
[3]	SEPARABLE BILATERAL FILTERING FOR FAST VIDEO PREPROCESSING by Tuan Q. Pham and Lucas J. van Vliet Quantitative Imaging Group, Department of Imaging Science and Technology Delft University of Technology

Parameters:

ioImage	image to be convolved.
iRadius	size of squared Gaussian kernel, the higher the slower.
iVarianceSpatial	variance of Gaussian spatial filter.
iVarianceRange	variance of Gaussian range filter.
iBorder	how to fill border.
iIteration	number of iterations. Default is 1.
iChannelMask	selected channels to be processed. Default is all channels.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

virtual bool eLynx::Image::IImageLocalProcessing::ApplyBoxBlur	(	AbstractImage &	ioImage,
		uint32	iWidth,
		uint32	iHeight,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Box blur filter, this is the blur filter with best performance with int64 kernel.

Implementation is based on this article:

[1]	Fast Image Convolutions by Wojciech Jarosz SIGGRAPH 2001

Parameters:

ioImage	image to blur.
iWidth	kernel width.
iHeight	kernel height.
iBorder	how to fill border.
iIteration	number of iterations.
iChannelMask	selected channels to be processed. Default is all.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

virtual bool eLynx::Image::IImageLocalProcessing::ApplyGaussian	(	AbstractImage &	ioImage,
		double	iRadius,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Gaussian filter smooths the current image by convolving a Gaussian kernel sized by iRadius and computed variance based of radius.

Parameters:

ioImage	image to be blured.
iRadius	size of squared Gaussian kernel.
iBorder	how to fill border.
iIteration	number of iterations.
iChannelMask	selected channels to be processed. Default is all.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

virtual bool eLynx::Image::IImageLocalProcessing::ApplyGaussian	(	AbstractImage &	ioImage,
		double	iRadius,
		double	iVariance,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Gaussian filter smooths the current image by convolving a Gaussian kernel sized by iRadius and with the selected iVariance.

Parameters:

ioImage	image to be blured.
iRadius	size of squared Gaussian kernel.
iVariance	variance of Gaussian curve.
iBorder	how to fill border.
iIteration	number of iterations.
iChannelMask	selected channels to be processed. Default is all.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

virtual bool eLynx::Image::IImageLocalProcessing::ApplyGaussian	(	AbstractImage &	ioImage,
		uint32	iWidth,
		uint32	iHeight,
		double	iVariance,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Gaussian filter smooths the current image by convolving a Gaussian kernel(iWidth,iHeight) with the selected iVariance.

Parameters:

ioImage	image to be blured.
iWidth	width of Gaussian kernel.
iHeight	height of Gaussian kernel.
iVariance	variance of Gaussian curve.
iBorder	how to fill border.
iIteration	number of iterations.
iChannelMask	selected channels to be processed. Default is all.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

virtual bool eLynx::Image::IImageLocalProcessing::ApplySelectiveBlur	(	AbstractImage &	ioImage,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Adaptive blur filter, this is a blur filter that protects edges.

Based on Selective blur by Daniel Lacroix.

Parameters:

ioImage	image to blur.
iBorder	how to fill border.
iIteration	number of iterations.
iChannelMask	selected channels to be processed. Default is all.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

virtual bool eLynx::Image::IImageLocalProcessing::Convolve	(	AbstractImage &	ioImage,
		const Math::ConvolutionKerneld &	iKernel,
		double	iThresholdMin,
		double	iThresholdMax,
		bool	ibAbsolute,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Convolve with a kernel on thresholded values.

Parameters:

ioImage	image to be convolved.
iKernel	the convolution kernel [WxH].
iThresholdMin	Threshold min to apply filter.
iThresholdMax	Threshold max to apply filter.
ibAbsolute	true to use absolute value of convolution, false otherwise.
iBorder	how to fill border.
iIteration	number of iterations.
iChannelMask	selected channels to be processed. Default is all.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

virtual bool eLynx::Image::IImageLocalProcessing::Convolve	(	AbstractImage &	ioImage,
		const Math::ConvolutionKerneld &	iKernel1,
		const Math::ConvolutionKerneld &	iKernel2,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Convolve with two separable kernels [Wx1] x [1xH].

Greatly improve performance compare to convolution with [WxH] filter. Algorithm descrition: Convolution with separative kernels

iBorder effects

Using iBorder with BF_Cycle on a cyclic image, image remains cyclic after convolution.

Parameters:

ioImage	image to be convolved.
iKernel1	a convolution kernel [Wx1] or [1xH].
iKernel2	a convolution kernel, if iKernel1 is [Wx1] must be [1xH], else [Wx1].
iBorder	how to fill border.
iIteration	number of iterations.
iChannelMask	selected channels to be processed. Default is all.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

virtual bool eLynx::Image::IImageLocalProcessing::Convolve	(	AbstractImage &	ioImage,
		const Math::ConvolutionKerneld &	iKernel,
		bool	ibAbsolute,
		EBorderFill	iBorder,
		uint32	iIteration,
		uint32	iChannelMask,
		ProgressNotifier &	iNotifier
	)		const `[pure virtual]`

Convolve with a kernel.

Parameters:

ioImage	image to be convolved.
iKernel	the convolution kernel [WxH].
ibAbsolute	true to use absolute value of convolution, false otherwise.
iBorder	how to fill border.
iIteration	number of iterations.
iChannelMask	selected channels to be processed. Default is all.
iNotifier	a notifier for progression, log and cancel.

Returns:: Method running status.

Implemented in eLynx::Image::ImageLocalProcessingImpl< Pixel >.

The documentation for this class was generated from the following file:

E:/dev/eLynx/include/elx/image/IImageLocalProcessing.h

eLynx::Image::IImageLocalProcessing Class Reference

Public Member Functions

Detailed Description

Member Function Documentation