Functions
array	filter (const array &image, const array &kernel)
	Image Filtering.
array	medfilt (const array &image, const unsigned height=3, const unsigned width=3)
	Median filtering within window (default 3x3)
array	bilateral (const array &image, const float space, const float color)
	Bilateral filtering.
array	meanshift (const array &image, const float space, const float color, const int iter=5)
	Meanshift filtering.
array	convolve (const array &f1, const array &f2, const array &signal, bool expand=false)
	Separable convolution (2D) with device arrays.
template<typename ty >
array	convolve (unsigned n1, const ty f1, unsigned n2, const ty f2, const array &signal, bool expand=false)
	Separable convolution (2D) with host arrays.
array	convolve (const array &signal, const array &filter, bool expand=false)
	Convolution (1D,2D,3D).
template<typename ty >
array	convolve (const array &signal, unsigned ndims, unsigned dims, const ty h_kernel, bool expand=false)
	Convolution (1D,2D,3D) with host filter.

Function Documentation

array af::filter	(	const array &	image,
		const array &	kernel
	)

Image Filtering.

       // filter (convolve) an image with a 3x3 sobel kernel
       const float h_kernel[] = { -2.0, -1.0,  0.0,
                                  -1.0,  0.0,  1.0,
                                   0.0,  1.0,  2.0 };
       array kernel = array(3,3,h_kernel);
       array img_out = filter(img_in, kernel);

Parameters:

[in]	image
[in]	kernel	coefficient matrix

Returns:: filtered image of same size as input

Note:: Output is same size as input. Filtering done using correlation. Array values outside bounds are assumed to have zero value (0).

array af::medfilt	(	const array &	image,
		const unsigned	height = `3`,
		const unsigned	width = `3`
	)

Median filtering within window (default 3x3)

       // median filter an image with a 5x5 kernel
       array img_out = medfilt(img_in, 5, 5);

       // median filter an image with the default 3x3 kernel
       array img_out = medfilt(img_in);

Parameters:

[in]	image
[in]	height	of window (default 3)
[in]	width	of window (default 3)

array af::bilateral	(	const array &	image,
		const float	space,
		const float	color
	)

Bilateral filtering.

       // bilateral filter an image with color values [0-1]
       float sigma_space = 2.f;
       float sigma_color = 0.1f;
       array img_out = bilateral(img_in, sigma_space, sigma_color);

       // bilateral filter an image with color values [0-255]
       float sigma_space = 2.f;
       float sigma_color = 0.1f * 255.f;
       array img_out = bilateral(img_in, sigma_space, sigma_color);

Parameters:

[in]	image	input image
[in]	space	radius in pixels, area for filtering. note: internally space *= 1.5
[in]	color	difference in color allowed, range depends on values in `image`

Note:: color range depends on values in the image if image is [0-1], scale color from [0-1]; if image is [0-255], scale color from [0-255];

array af::meanshift	(	const array &	image,
		const float	space,
		const float	color,
		const int	iter = `5`
	)

Meanshift filtering.

       // meanshift filter an image with color values [0-1]
       float sigma_space = 3.f;
       float sigma_color = 0.2f;
       int   iterations  = 5;
       array img_out = meanshift(img_in, sigma_space, sigma_color, iterations);

       // meanshift filter an image with color values [0-255]
       float sigma_space = 3.f;
       float sigma_color = 0.2f * 255.f;
       int   iterations  = 5;
       array img_out = meanshift(img_in, sigma_space, sigma_color, iterations);

Parameters:

[in]	image	input image
[in]	space	radius in pixels, area for filtering. note: internally space *= 1.5
[in]	color	difference in color allowed, range depends on values in `image`
[in]	iter	maximum number of iterations for convergence (default=5, max=100)

Note:: color range depends on values in the image if image is [0-1], scale color from [0-1]; if image is [0-255], scale color from [0-255];

array af::convolve	(	const array &	f1,
		const array &	f2,
		const array &	signal,
		bool	expand = `false`
	)

Separable convolution (2D) with device arrays.

Parameters:

[in]	f1	filter along the columns (first dimension)
[in]	f2	filter along the rows (second dimension)
[in]	signal
[in]	expand	Performs expanded convolution if true. Default is false

Examples:: examples/getting_started/convolve.cpp, examples/image_processing/image_demo.cpp, examples/image_processing/optical_flow.cpp, and examples/pde/swe.cpp.

array af::convolve	(	unsigned	n1,
		const ty *	f1,
		unsigned	n2,
		const ty *	f2,
		const array &	signal,
		bool	expand = `false`
	)

Separable convolution (2D) with host arrays.

Parameters:

[in]	n1	number of elements in `f1`
[in]	f1	host pointer containing the column filter
[in]	n2	number of elements in `f2`
[in]	f2	host pointer containing the row filter
[in]	signal
[in]	expand	Performs expanded convolution if true. Default is false

array af::convolve	(	const array &	signal,
		const array &	filter,
		bool	expand = `false`
	)

Convolution (1D,2D,3D).

   array x = randu(5);
   print(x);
   array f = constant(1,3);
   // 2D convolution, 3x3 filter
   array c = convolve(x,f);
   print(c);

Parameters:

[in]	signal
[in]	filter
[in]	expand	Performs expanded convolution if true. Default is false

array af::convolve	(	const array &	signal,
		unsigned	ndims,
		unsigned *	dims,
		const ty *	h_kernel,
		bool	expand = `false`
	)

Convolution (1D,2D,3D) with host filter.

   array x = randu(5);
   print(x);
   array f = constant(1,3);
   // 2D convolution, 3x3 filter
   float f[] = {0,1,0,1,0,1,0,1,0};
   unsigned d[] = {3,3};
   array c = convolve(x,2,d,f);
   print(c);

Parameters:

[in]	signal
[in]	ndims	Number of dimensions for the filter `h_kernel`
[in]	dims	Array containing dimension sizes of filter `h_kernel`
[in]	h_kernel	Host-side array containing the filter kernel coefficients
[in]	expand	Performs expanded convolution if true. Default is false

Image filtering & convolutions

Functions

Function Documentation