Operator Reference

HALCON Operator Reference / Filters / Smoothing
ClassesClasses | | Operators

sigma_imagesigma_imageSigmaImageSigmaImagesigma_image (Operator)

sigma_imagesigma_imageSigmaImageSigmaImagesigma_image — Non-linear smoothing with the sigma filter.

Signature

sigma_image(Image : ImageSigma : MaskHeight, MaskWidth, Sigma : )

Herror sigma_image(const Hobject Image, Hobject* ImageSigma, const Hlong MaskHeight, const Hlong MaskWidth, const Hlong Sigma)

Herror T_sigma_image(const Hobject Image, Hobject* ImageSigma, const Htuple MaskHeight, const Htuple MaskWidth, const Htuple Sigma)

void SigmaImage(const HObject& Image, HObject* ImageSigma, const HTuple& MaskHeight, const HTuple& MaskWidth, const HTuple& Sigma)

HImage HImage::SigmaImage(Hlong MaskHeight, Hlong MaskWidth, Hlong Sigma) const

static void HOperatorSet.SigmaImage(HObject image, out HObject imageSigma, HTuple maskHeight, HTuple maskWidth, HTuple sigma)

HImage HImage.SigmaImage(int maskHeight, int maskWidth, int sigma)

def sigma_image(image: HObject, mask_height: int, mask_width: int, sigma: int) -> HObject

Description

The operator sigma_imagesigma_imageSigmaImageSigmaImagesigma_image carries out a non-linear smoothing of the gray values of all input images (ImageImageImageimageimage). All pixels in a rectangular window (MaskHeight x MaskWidth) are used to determine the new gray value of the central pixel of this window. First, the gray value standard deviation of all pixels in the window is calculated. Then, all pixels of the window with a gray value that differs from the gray value of the central pixel by less than SigmaSigmaSigmasigmasigma times this standard deviation are used to calculate the new gray value of the central pixel. The gray value of the central pixel is the average of the gray values of the selected pixels. If no pixel could be selected for the averaging of the gray values, the gray value of the central pixel remains unchanged.

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

Attention

If even values instead of odd values are given for MaskHeightMaskHeightMaskHeightmaskHeightmask_height or MaskWidthMaskWidthMaskWidthmaskWidthmask_width, the routine uses the next larger odd values instead (this way the center of the filter mask is always explicitly determined).

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

  • 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

ImageImageImageimageimage (input_object)  (multichannel-)image(-array) → objectHImageHObjectHObjectHobject (byte / cyclic / int1 / int2 / uint2 / int4 / real)

Image to be smoothed.

ImageSigmaImageSigmaImageSigmaimageSigmaimage_sigma (output_object)  (multichannel-)image(-array) → objectHImageHObjectHObjectHobject * (byte / cyclic / int1 / int2 / uint2 / int4 / real)

Smoothed image.

MaskHeightMaskHeightMaskHeightmaskHeightmask_height (input_control)  extent.y → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Height of the mask (number of lines).

Default: 5

Suggested values: 3, 5, 7, 9, 11, 13, 15

Value range: 3 ≤ MaskHeight MaskHeight MaskHeight maskHeight mask_height

Minimum increment: 2

Recommended increment: 2

Restriction: odd(MaskHeight)

MaskWidthMaskWidthMaskWidthmaskWidthmask_width (input_control)  extent.x → HTupleintHTupleHtuple (integer) (int / long) (Hlong) (Hlong)

Width of the mask (number of columns).

Default: 5

Suggested values: 3, 5, 7, 9, 11, 13, 15

Value range: 3 ≤ MaskWidth MaskWidth MaskWidth maskWidth mask_width

Minimum increment: 2

Recommended increment: 2

Restriction: odd(MaskWidth)

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

Max. deviation to the average.

Default: 3

Suggested values: 3, 5, 7, 9, 11, 20, 30, 50

Value range: 0 ≤ Sigma Sigma Sigma sigma sigma

Minimum increment: 1

Recommended increment: 2

Example (HDevelop)

read_image(Image,'fabrik')
sigma_image(Image,ImageSigma,5,5,3)
dev_display(ImageSigma)

Example (C)

read_image(&Image,"fabrik");
sigma_image(Image,&ImageSigma,5,5,3);
disp_image(ImageSigma,WindowHandle);

Example (HDevelop)

read_image(Image,'fabrik')
sigma_image(Image,ImageSigma,5,5,3)
dev_display(ImageSigma)

Example (HDevelop)

read_image(Image,'fabrik')
sigma_image(Image,ImageSigma,5,5,3)
dev_display(ImageSigma)

Complexity

For each pixel: O(MaskHeight*MaskWidth).

Result

If the parameter values are correct the operator sigma_imagesigma_imageSigmaImageSigmaImagesigma_image 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>)set_system("no_object_result",<Result>). If necessary an exception is raised.

Possible Predecessors

read_imageread_imageReadImageReadImageread_image

Possible Successors

thresholdthresholdThresholdThresholdthreshold, dyn_thresholddyn_thresholdDynThresholdDynThresholddyn_threshold, regiongrowingregiongrowingRegiongrowingRegiongrowingregiongrowing

Alternatives

anisotropic_diffusionanisotropic_diffusionAnisotropicDiffusionAnisotropicDiffusionanisotropic_diffusion, rank_imagerank_imageRankImageRankImagerank_image

See also

smooth_imagesmooth_imageSmoothImageSmoothImagesmooth_image, binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter, gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter, mean_imagemean_imageMeanImageMeanImagemean_image

References

R. Haralick, L. Shapiro; “Computer and Robot Vision”; Addison-Wesley, 1992, Seite 325

Module

Foundation

ClassesClasses | | Operators