The C interface for histogram. More...

afError	af_histogram_S (float d_hist, unsigned length, const float d_data, unsigned nbins, const float *h_bins, unsigned nsets, unsigned ngfor)
	Form a non-normalized histogram from input matrix. More...

afError	af_histminmax_S (float d_hist, unsigned len, const float d_data, unsigned bins, const float *h_data, unsigned nsets, unsigned ngfor, float min, float max)
	Form a non-normalized histogram from input matrix, using the specified minimum and maximum range for binning. More...

Detailed Description

The C interface for histogram.

A histogram is a representation of the distribution of data in an image. This representation is essentially a graph consisting of the data range or domain on one axis and frequency of occurence on the other axis. All the data in the domain is counted in the appropriate bin. The total number of elements belonging to each bin is known as the bin's frequency.

The regular histogram function creates bins of equal size between the minimum and maximum of the input data (calculated internally). The histogram min-max function takes input parameters minimum and maximum, and divides the bins into equal sizes within the range specified by min and max parameters. All values less than min in the data range are placed in the first (min) bin and all values greater than max will be placed in the last (max) bin.

// Create a histogram using 256 bins
array hist_out = histogram(hist_in, 256);
// Histogram with explicit min/max
// generate sample input data
// generates an array with 50 elements from -25 to 24.
array hist_in = seq(-25, 24)
// Create histogram using 10 bins,with bins scaled from 1 to 10
// bin[0] gets -inf to 1
// bin[9] gets   10 to inf
array hist_out = histogram(img_in, 10, 0, 10);
// hist_out will be [26, 1, 1, 1, 1, 1, 1, 1, 1, 16]

Data normalization via histogram equalization

// img_in and img_out are single channel images
array ihist = histogram(img_in, 256);
array img_out = histequal(img_in, ihist);

Function Documentation

afError af_histogram_S	(	float *	d_hist,
		unsigned	length,
		const float *	d_data,
		unsigned	nbins,
		const float *	h_bins,
		unsigned	nsets,
		unsigned	ngfor
	)

Form a non-normalized histogram from input matrix.

Parameters

[out]	d_hist	Count of occurrences - PxN matrix
[in]	length	Length of input matrix `d_data` - N
[in]	d_data	Device-side vector or matrix - MxN
[in]	nbins	Number of bins in `h_bins` - P
[in]	h_bins	Host-side vector indicating center of each bin (can be NULL)
[in]	nsets	Number of rows in input data - M
[in]	ngfor	Number of gfor passes

Note: d_hist is: a 1xP vector hist for vector inputs, or a PxN matrix hist for MxN matrix inputsSingle-precision histogram calculation

afError af_histminmax_S	(	float *	d_hist,
		unsigned	len,
		const float *	d_data,
		unsigned	bins,
		const float *	h_data,
		unsigned	nsets,
		unsigned	ngfor,
		float	min,
		float	max
	)

Form a non-normalized histogram from input matrix, using the specified minimum and maximum range for binning.

Parameters

[out]	d_hist	Count of occurrences - PxN matrix
[in]	len	Length of input matrix `d_data` - N
[in]	d_data	Device-side vector or matrix - MxN
[in]	bins	Number of bins in `h_bins` - P
[in]	h_data	Host-side vector indicating center of each bin (can be NULL)
[in]	nsets	Number of rows in input data - M
[in]	ngfor	Number of gfor passes
[in]	min	Minimum binned value (eg. 0)
[in]	max	Maximum binned value (eg. 255)

Note: d_hist is: a 1xP vector hist for vector inputs, or a PxN matrix hist for MxN matrix inputsSingle-precision histogram calculation