convolve

C++ interface for Convolution. More...

array	convolve (const array &f1, const array &f2, const array &signal, bool expand=false)
	Separable convolution (2D) with device arrays. More...
template<typename ty >
array	convolve (unsigned n1, const ty *h_f1, unsigned n2, const ty *h_f2, const array &signal, bool expand=false)
	Separable convolution (2D) with host arrays. More...
array	convolve (const array &signal, const array &filter, bool expand=false)
	Convolution (1D,2D,3D). More...
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. More...

Detailed Description

C++ interface for Convolution.

A convolution is a common operation between a source array, a, and a filter (or kernel) array b. The answer to the convolution is the same as computing the coefficients in polynomial multiplication, if a and b are the coefficients.

Another way to think about it is that the filter kernel is centered on each pixel in a, and the output for that pixel or data point is the sum of the products.

Consider the following example with the calculation for the first few points shown as a comment:

array a = seq(1, 8);
//a = 1.0000
//    2.0000
//    3.0000
//    4.0000
//    5.0000
//    6.0000
//    7.0000
//    8.0000

array b = seq(0, 2);
b = pow2(b);
//b = 1.0000
//    2.0000
//    4.0000

array out = convolve(a,b);
//out = 4.0000 (0*4)+(1*2)+(2*1)
//     11.0000 (1*4)+(2*2)+(3*1)
//     18.0000 (2*4)+(3*2)+(4*1)
//     25.0000 ...
//     32.0000
//     39.0000
//     46.0000
//     44.0000

Note that pixels that are outside an image or data points that are outside the domain of a signal are treated as zero.

Function Documentation

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 *	h_f1,
		unsigned	n2,
		const ty *	h_f2,
		const array &	signal,
		bool	expand = false
	)

Separable convolution (2D) with host arrays.

Parameters

[in]	n1	number of elements in f1
[in]	h_f1	host pointer containing the column filter
[in]	n2	number of elements in f2
[in]	h_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