Operator Reference

HALCON Operator Reference / Filters / Smoothing
ClassesClasses | | Operators

mean_imagemean_imageMeanImageMeanImagemean_image (Operator)

mean_imagemean_imageMeanImageMeanImagemean_image — Smooth by averaging.

Signature

mean_image(Image : ImageMean : MaskWidth, MaskHeight : )

Herror mean_image(const Hobject Image, Hobject* ImageMean, const Hlong MaskWidth, const Hlong MaskHeight)

Herror T_mean_image(const Hobject Image, Hobject* ImageMean, const Htuple MaskWidth, const Htuple MaskHeight)

void MeanImage(const HObject& Image, HObject* ImageMean, const HTuple& MaskWidth, const HTuple& MaskHeight)

HImage HImage::MeanImage(Hlong MaskWidth, Hlong MaskHeight) const

static void HOperatorSet.MeanImage(HObject image, out HObject imageMean, HTuple maskWidth, HTuple maskHeight)

HImage HImage.MeanImage(int maskWidth, int maskHeight)

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

Description

The operator mean_imagemean_imageMeanImageMeanImagemean_image carries out a linear smoothing with the gray values of all input images (ImageImageImageimageimage). The filter matrix consists of ones (evaluated equally) and has the size MaskHeight x MaskWidth. The result of the convolution is divided by MaskHeight x MaskWidth. For border treatment the gray values are reflected at the image edges.

For mean_imagemean_imageMeanImageMeanImagemean_image special optimizations are implemented that use SIMD technology. The actual application of these special optimizations is controlled by the system parameter 'mmx_enable'"mmx_enable""mmx_enable""mmx_enable""mmx_enable" (see set_systemset_systemSetSystemSetSystemset_system). If 'mmx_enable'"mmx_enable""mmx_enable""mmx_enable""mmx_enable" is set to 'true'"true""true""true""true" (and the SIMD instruction set is available), the internal calculations are performed using SIMD technology. Note that SIMD technology performs best on large, compact input regions. Depending on the input region and the capabilities of the hardware the execution of mean_imagemean_imageMeanImageMeanImagemean_image might even take significantly more time with SIMD technology than without.

At any rate, it is advantageous for the performance of mean_imagemean_imageMeanImageMeanImagemean_image to choose the input region of ImageImageImageimageimage such that any border treatment is avoided.

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).

The mean filter value on real images is calculated internally using single precision floating point. This can lead to overflows (and thus incorrect results) if the full dynamic range is used.

mean_imagemean_imageMeanImageMeanImagemean_image can be executed on OpenCL devices for byte, int2, uint2, int4 and real images if MaskHeightMaskHeightMaskHeightmaskHeightmask_height is less than twice the height of ImageImageImageimageimage. For OpenCL, the mean filter value is calculated internally using either 32 bit signed integers (for all integer image types) or single precision floating point (for real images). This can lead to overflows (and thus incorrect results) if ImageImageImageimageimage is either an int4 or real image and the full dynamic range is used. Additionally, to improve performance a full scan of each row of ImageImageImageimageimage is calculated (again using either 32 bit integer or single precision floating point arithmetic) if MaskWidthMaskWidthMaskWidthmaskWidthmask_width is bigger than 9. This can also lead to overflows with very wide images even for byte, int2, or uint2 images. In these cases, the CPU version of mean_imagemean_imageMeanImageMeanImagemean_image should be used.

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

ImageImageImageimageimage (input_object)  (multichannel-)image(-array) → objectHImageHObjectHObjectHobject (byte* / int2* / uint2* / int4* / int8 / real* / vector_field) *allowed for compute devices

Image to be smoothed.

ImageMeanImageMeanImageMeanimageMeanimage_mean (output_object)  (multichannel-)image(-array) → objectHImageHObjectHObjectHobject * (byte / int2 / uint2 / int4 / int8 / real / vector_field)

Smoothed image.

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

Width of filter mask.

Default: 9

Suggested values: 3, 5, 7, 9, 11, 15, 23, 31, 43, 61, 101

Value range: 1 ≤ MaskWidth MaskWidth MaskWidth maskWidth mask_width

Minimum increment: 2

Recommended increment: 2

Restriction: odd(MaskWidth) && MaskWidth < width(Image) * 2

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

Height of filter mask.

Default: 9

Suggested values: 3, 5, 7, 9, 11, 15, 23, 31, 43, 61, 101

Value range: 1 ≤ MaskHeight MaskHeight MaskHeight maskHeight mask_height

Minimum increment: 2

Recommended increment: 2

Restriction: odd(MaskHeight) && MaskHeight < height(Image) * 2

Example (HDevelop)

read_image(Image,'fabrik')
mean_image(Image,Mean,3,3)
dev_display(Mean)

Example (C)

read_image(&Image,"fabrik");
mean_image(Image,&Mean,3,3);
disp_image(Mean,WindowHandle);

Example (HDevelop)

read_image(Image,'fabrik')
mean_image(Image,Mean,3,3)
dev_display(Mean)

Example (HDevelop)

read_image(Image,'fabrik')
mean_image(Image,Mean,3,3)
dev_display(Mean)

Complexity

For each pixel: O(15).

Result

If the parameter values are correct the operator mean_imagemean_imageMeanImageMeanImagemean_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

reduce_domainreduce_domainReduceDomainReduceDomainreduce_domain, rectangle1_domainrectangle1_domainRectangle1DomainRectangle1Domainrectangle1_domain

Possible Successors

dyn_thresholddyn_thresholdDynThresholdDynThresholddyn_threshold, regiongrowingregiongrowingRegiongrowingRegiongrowingregiongrowing

Alternatives

binomial_filterbinomial_filterBinomialFilterBinomialFilterbinomial_filter, gauss_filtergauss_filterGaussFilterGaussFiltergauss_filter, smooth_imagesmooth_imageSmoothImageSmoothImagesmooth_image, mean_image_shapemean_image_shapeMeanImageShapeMeanImageShapemean_image_shape

See also

anisotropic_diffusionanisotropic_diffusionAnisotropicDiffusionAnisotropicDiffusionanisotropic_diffusion, sigma_imagesigma_imageSigmaImageSigmaImagesigma_image, convol_imageconvol_imageConvolImageConvolImageconvol_image, gen_lowpassgen_lowpassGenLowpassGenLowpassgen_lowpass

Module

Foundation

ClassesClasses | | Operators