smooth_imagesmooth_imageSmoothImageSmoothImagesmooth_image (Operator)

Name

smooth_imagesmooth_imageSmoothImageSmoothImagesmooth_image — Smooth an image using various filters.

Signature

smooth_image(Image : ImageSmooth : Filter, Alpha : )

Herror smooth_image(const Hobject Image, Hobject* ImageSmooth, const char* Filter, double Alpha)

Herror T_smooth_image(const Hobject Image, Hobject* ImageSmooth, const Htuple Filter, const Htuple Alpha)

void SmoothImage(const HObject& Image, HObject* ImageSmooth, const HTuple& Filter, const HTuple& Alpha)

HImage HImage::SmoothImage(const HString& Filter, double Alpha) const

HImage HImage::SmoothImage(const char* Filter, double Alpha) const

HImage HImage::SmoothImage(const wchar_t* Filter, double Alpha) const   (Windows only)

static void HOperatorSet.SmoothImage(HObject image, out HObject imageSmooth, HTuple filter, HTuple alpha)

HImage HImage.SmoothImage(string filter, double alpha)

def smooth_image(image: HObject, filter: str, alpha: float) -> HObject

Description

smooth_imagesmooth_imageSmoothImageSmoothImageSmoothImagesmooth_image smooths gray images using recursive filters originally developed by Deriche and Shen and using the non-recursive Gaussian filter. The following filters can be chosen via the parameter FilterFilterFilterFilterfilterfilter: 'deriche1', 'deriche2', 'shen' and 'gauss'. The “filter width” (i.e., the range of the filter and thereby result of the filter) can be of any size. In the case that the Deriche or Shen is chosen it decreases by increasing the filter parameter AlphaAlphaAlphaAlphaalphaalpha and increases in the case of the Gauss filter (and AlphaAlphaAlphaAlphaalphaalpha corresponds to the standard deviation of the Gaussian function). An approximation of the appropriate size of the filter width AlphaAlphaAlphaAlphaalphaalpha is performed by the operator info_smoothinfo_smoothInfoSmoothInfoSmoothInfoSmoothinfo_smooth.

Non-recursive filters like the Gaussian filter are often implemented using filter-masks. In this case the runtime of the operator increases with increasing size of the filter mask. The runtime of the recursive filters remains constant; except the border treatment becomes a little bit more time consuming. The Gaussian filter becomes slow in comparison to the recursive ones but is in contrast to them isotropic (the filter 'deriche2' is only weakly direction sensitive). A comparable result of the smoothing is achieved by choosing the following values for the parameter: Alpha(deriche2) = Alpha(deriche1) / 2, Alpha(shen) = Alpha(deriche1) / 2, Alpha(gauss) = 1.77 / Alpha(deriche1).

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

Parameters

ImageImageImageImageimageimage (input_object)  (multichannel-)image(-array) objectHImageHObjectHImageHobject (byte / uint2 / real)

Image to be smoothed.

ImageSmoothImageSmoothImageSmoothImageSmoothimageSmoothimage_smooth (output_object)  (multichannel-)image(-array) objectHImageHObjectHImageHobject * (byte / uint2 / real)

Smoothed image.

FilterFilterFilterFilterfilterfilter (input_control)  string HTuplestrHTupleHtuple (string) (string) (HString) (char*)

Filter.

Default value: 'deriche2' "deriche2" "deriche2" "deriche2" "deriche2" "deriche2"

List of values: 'deriche1'"deriche1""deriche1""deriche1""deriche1""deriche1", 'deriche2'"deriche2""deriche2""deriche2""deriche2""deriche2", 'gauss'"gauss""gauss""gauss""gauss""gauss", 'shen'"shen""shen""shen""shen""shen"

AlphaAlphaAlphaAlphaalphaalpha (input_control)  real HTuplefloatHTupleHtuple (real) (double) (double) (double)

Filter parameter: small values cause strong smoothing (vice versa by using 'gauss'"gauss""gauss""gauss""gauss""gauss").

Default value: 0.5

Suggested values: 0.1, 0.2, 0.3, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0, 4.0, 5.0, 7.0, 10.0

Minimum increment: 0.01

Recommended increment: 0.1

Restriction: Alpha > 0

Example (HDevelop)

info_smooth('deriche2',0.5,Size,Coeffs)
smooth_image(Input,Smooth,'deriche2',7)

Example (C)

info_smooth('deriche2',0.5,Size,Coeffs);
smooth_image(Input,&Smooth,'deriche2',7);

Example (HDevelop)

info_smooth('deriche2',0.5,Size,Coeffs)
smooth_image(Input,Smooth,'deriche2',7)

Example (HDevelop)

info_smooth('deriche2',0.5,Size,Coeffs)
smooth_image(Input,Smooth,'deriche2',7)

Example (HDevelop)

info_smooth('deriche2',0.5,Size,Coeffs)
smooth_image(Input,Smooth,'deriche2',7)

Result

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

Possible Predecessors

read_imageread_imageReadImageReadImageReadImageread_image

Possible Successors

thresholdthresholdThresholdThresholdThresholdthreshold, dyn_thresholddyn_thresholdDynThresholdDynThresholdDynThresholddyn_threshold, regiongrowingregiongrowingRegiongrowingRegiongrowingRegiongrowingregiongrowing

Alternatives

binomial_filterbinomial_filterBinomialFilterBinomialFilterBinomialFilterbinomial_filter, gauss_filtergauss_filterGaussFilterGaussFilterGaussFiltergauss_filter, mean_imagemean_imageMeanImageMeanImageMeanImagemean_image, derivate_gaussderivate_gaussDerivateGaussDerivateGaussDerivateGaussderivate_gauss, isotropic_diffusionisotropic_diffusionIsotropicDiffusionIsotropicDiffusionIsotropicDiffusionisotropic_diffusion

See also

info_smoothinfo_smoothInfoSmoothInfoSmoothInfoSmoothinfo_smooth, median_imagemedian_imageMedianImageMedianImageMedianImagemedian_image, sigma_imagesigma_imageSigmaImageSigmaImageSigmaImagesigma_image, anisotropic_diffusionanisotropic_diffusionAnisotropicDiffusionAnisotropicDiffusionAnisotropicDiffusionanisotropic_diffusion

References

R.Deriche: “Fast Algorithms for Low-Level Vision”; IEEE Transactions on Pattern Analysis and Machine Intelligence; PAMI-12, no. 1; S. 78-87; 1990.

Module

Foundation