Operator Reference

HALCON Operator Reference / Filters / Noise
ClassesClasses | | Operators

noise_distribution_meanT_noise_distribution_meanNoiseDistributionMeanNoiseDistributionMeannoise_distribution_mean (Operator)

noise_distribution_meanT_noise_distribution_meanNoiseDistributionMeanNoiseDistributionMeannoise_distribution_mean — Determine the noise distribution of an image.

Signature

noise_distribution_mean(ConstRegion, Image : : FilterSize : Distribution)

Herror T_noise_distribution_mean(const Hobject ConstRegion, const Hobject Image, const Htuple FilterSize, Htuple* Distribution)

void NoiseDistributionMean(const HObject& ConstRegion, const HObject& Image, const HTuple& FilterSize, HTuple* Distribution)

HTuple HImage::NoiseDistributionMean(const HRegion& ConstRegion, Hlong FilterSize) const

HTuple HRegion::NoiseDistributionMean(const HImage& Image, Hlong FilterSize) const

static void HOperatorSet.NoiseDistributionMean(HObject constRegion, HObject image, HTuple filterSize, out HTuple distribution)

HTuple HImage.NoiseDistributionMean(HRegion constRegion, int filterSize)

HTuple HRegion.NoiseDistributionMean(HImage image, int filterSize)

def noise_distribution_mean(const_region: HObject, image: HObject, filter_size: int) -> Sequence[float]

Description

noise_distribution_meannoise_distribution_meanNoiseDistributionMeanNoiseDistributionMeannoise_distribution_mean calculates the noise distribution in a region of the image ImageImageImageimageimage. The parameter ConstRegionConstRegionConstRegionconstRegionconst_region determines a region of the image with approximately constant gray values. Ideally, the changes in gray values should only be caused by noise in this region. From this region the noise distribution is determined by using the mean_imagemean_imageMeanImageMeanImagemean_image operator to smooth the image, and to use the gray value differences in this area as an estimate for the noise distribution, which is returned in DistributionDistributionDistributiondistributiondistribution.

Attention

It is important to ensure that the region ConstRegionConstRegionConstRegionconstRegionconst_region is not too close to a large gradient in the image, because the gradient values are then used for calculating the mean. This means the distance of ConstRegionConstRegionConstRegionconstRegionconst_region must be at least as large as the filter size FilterSizeFilterSizeFilterSizefilterSizefilter_size used for calculating the mean.

Execution Information

  • Multithreading type: reentrant (runs in parallel with non-exclusive operators).
  • Multithreading scope: global (may be called from any thread).
  • Processed without parallelization.

Parameters

ConstRegionConstRegionConstRegionconstRegionconst_region (input_object)  region(-array) → objectHRegionHObjectHObjectHobject

Region from which the noise distribution is to be estimated.

ImageImageImageimageimage (input_object)  singlechannelimage → objectHImageHObjectHObjectHobject (byte)

Corresponding image.

FilterSizeFilterSizeFilterSizefilterSizefilter_size (input_control)  integer → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Size of the mean filter.

Default: 21

Suggested values: 5, 11, 15, 21, 31, 51, 101

Value range: 3 ≤ FilterSize FilterSize FilterSize filterSize filter_size ≤ 501 (lin)

Minimum increment: 2

Recommended increment: 2

DistributionDistributionDistributiondistributiondistribution (output_control)  distribution.values-array → HTupleSequence[float]HTupleHtuple (real) (double) (double) (double)

Noise distribution of all input regions.

Possible Predecessors

draw_regiondraw_regionDrawRegionDrawRegiondraw_region, gen_circlegen_circleGenCircleGenCirclegen_circle, gen_ellipsegen_ellipseGenEllipseGenEllipsegen_ellipse, gen_rectangle1gen_rectangle1GenRectangle1GenRectangle1gen_rectangle1, gen_rectangle2gen_rectangle2GenRectangle2GenRectangle2gen_rectangle2, thresholdthresholdThresholdThresholdthreshold, erosion_circleerosion_circleErosionCircleErosionCircleerosion_circle, binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter, gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter, smooth_imagesmooth_imageSmoothImageSmoothImagesmooth_image, sub_imagesub_imageSubImageSubImagesub_image

Possible Successors

add_noise_distributionadd_noise_distributionAddNoiseDistributionAddNoiseDistributionadd_noise_distribution

See also

mean_imagemean_imageMeanImageMeanImagemean_image, gauss_distributiongauss_distributionGaussDistributionGaussDistributiongauss_distribution

Module

Foundation

ClassesClasses | | Operators