Rank Convolution Operations [Image Processing]

Collaboration diagram for Rank Convolution Operations:

Functions
int	imProcessMedianConvolve (const imImage *src_image, imImage *dst_image, int kernel_size)
int	imProcessRangeConvolve (const imImage *src_image, imImage *dst_image, int kernel_size)
int	imProcessRankClosestConvolve (const imImage *src_image, imImage *dst_image, int kernel_size)
int	imProcessRankMaxConvolve (const imImage *src_image, imImage *dst_image, int kernel_size)
int	imProcessRankMinConvolve (const imImage *src_image, imImage *dst_image, int kernel_size)

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Detailed Description

All the rank convolution use the same base function. Near the border the base function includes only the real image pixels in the rank. No border extensions are used.

See im_process_loc.h

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Function Documentation

int imProcessMedianConvolve	(	const imImage *	src_image,
		imImage *	dst_image,
		int	kernel_size
	)

Rank convolution using the median value.
Returns zero if the counter aborted.
Supports all data types except complex. Can be applied on color images.

im.ProcessMedianConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] 

im.ProcessMedianConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] 

int imProcessRangeConvolve	(	const imImage *	src_image,
		imImage *	dst_image,
		int	kernel_size
	)

Rank convolution using (maximum-minimum) value.
Returns zero if the counter aborted.
Supports all data types except complex. Can be applied on color images.

im.ProcessRangeConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] 

im.ProcessRangeConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] 

int imProcessRankClosestConvolve	(	const imImage *	src_image,
		imImage *	dst_image,
		int	kernel_size
	)

Rank convolution using the closest maximum or minimum value.
Returns zero if the counter aborted.
Supports all data types except complex. Can be applied on color images.

im.ProcessRankClosestConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] 

im.ProcessRankClosestConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] 

int imProcessRankMaxConvolve	(	const imImage *	src_image,
		imImage *	dst_image,
		int	kernel_size
	)

Rank convolution using the maximum value.
Returns zero if the counter aborted.
Supports all data types except complex. Can be applied on color images.

im.ProcessRankMaxConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] 

im.ProcessRankMaxConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5] 

int imProcessRankMinConvolve	(	const imImage *	src_image,
		imImage *	dst_image,
		int	kernel_size
	)

Rank convolution using the minimum value.
Returns zero if the counter aborted.
Supports all data types except complex. Can be applied on color images.

im.ProcessRankMinConvolve(src_image: imImage, dst_image: imImage, kernel_size: number) -> counter: boolean [in Lua 5] 

im.ProcessRankMinConvolveNew(image: imImage, kernel_size: number) -> counter: boolean, new_image: imImage [in Lua 5]