binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter (Operator)

Name

binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter — Smooth an image using the binomial filter.

Signature

Description

binomial_filterbinomial_filterBinomialFilterBinomialFilterBinomialFilterbinomial_filter smooths the image ImageImageImageImageimageimage using a binomial filter with a mask size of MaskWidthMaskWidthMaskWidthMaskWidthmaskWidthmask_width * MaskHeightMaskHeightMaskHeightMaskHeightmaskHeightmask_height pixels and returns the smoothed image in ImageBinomialImageBinomialImageBinomialImageBinomialimageBinomialimage_binomial. The binomial filter is a very good approximation of a Gaussian filter that can be implemented extremely efficiently using only integer operations. Hence, binomial_filterbinomial_filterBinomialFilterBinomialFilterBinomialFilterbinomial_filter is very fast. Let m = MaskHeightMaskHeightMaskHeightMaskHeightmaskHeightmask_height and n = MaskWidthMaskWidthMaskWidthMaskWidthmaskWidthmask_width. Then, the filter coefficients are given by binomial coefficients as follows: Here, i = 0, ..., m-1 and j = 0, ..., n-1. The binomial filter performs approximately the same smoothing as a Gaussian filter with , where for simplicity it is assumed that m = n. In detail, the relationship between n and is:

If different values are chosen for MaskHeightMaskHeightMaskHeightMaskHeightmaskHeightmask_height and MaskWidthMaskWidthMaskWidthMaskWidthmaskWidthmask_width, the above relation between n and still holds and refers to the amount of smoothing in the row and column directions.

binomial_filterbinomial_filterBinomialFilterBinomialFilterBinomialFilterbinomial_filter can be executed on OpenCL devices for all supported image types.

For an explanation of the concept of smoothing filters see the introduction of chapter Filters / Smoothing.

Attention

Note that filter operators may return unexpected results if an image with a reduced domain is used as input. Please refer to the chapter Filters.

Execution Information

• Supports OpenCL compute devices.
• Multithreading type: reentrant (runs in parallel with non-exclusive operators).
• Multithreading scope: global (may be called from any thread).
• Automatically parallelized on tuple level.
• Automatically parallelized on channel level.
• Automatically parallelized on domain level.

Parameters

Result

If the parameter values are correct the operator binomial_filterbinomial_filterBinomialFilterBinomialFilterBinomialFilterbinomial_filter returns the value 2 ( H_MSG_TRUE) . The behavior in case of empty input (no input images available) is set via the operator set_system('no_object_result',<Result>)set_system("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)SetSystem("no_object_result",<Result>)set_system("no_object_result",<Result>). If necessary an exception is raised.

Possible Predecessors

read_imageread_imageReadImageReadImageReadImageread_image, grab_imagegrab_imageGrabImageGrabImageGrabImagegrab_image

Possible Successors

regiongrowingregiongrowingRegiongrowingRegiongrowingRegiongrowingregiongrowing, thresholdthresholdThresholdThresholdThresholdthreshold, sub_imagesub_imageSubImageSubImageSubImagesub_image, dyn_thresholddyn_thresholdDynThresholdDynThresholdDynThresholddyn_threshold, auto_thresholdauto_thresholdAutoThresholdAutoThresholdAutoThresholdauto_threshold

Alternatives

gauss_filtergauss_filterGaussFilterGaussFilterGaussFiltergauss_filter, smooth_imagesmooth_imageSmoothImageSmoothImageSmoothImagesmooth_image, derivate_gaussderivate_gaussDerivateGaussDerivateGaussDerivateGaussderivate_gauss, isotropic_diffusionisotropic_diffusionIsotropicDiffusionIsotropicDiffusionIsotropicDiffusionisotropic_diffusion

See also

mean_imagemean_imageMeanImageMeanImageMeanImagemean_image, anisotropic_diffusionanisotropic_diffusionAnisotropicDiffusionAnisotropicDiffusionAnisotropicDiffusionanisotropic_diffusion, sigma_imagesigma_imageSigmaImageSigmaImageSigmaImagesigma_image, gen_lowpassgen_lowpassGenLowpassGenLowpassGenLowpassgen_lowpass

Module

Foundation