gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage (Operator)

Name

gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage — Smooth an image using discrete Gaussian functions.

Warning

gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage is obsolete and is only provided for reasons of backward compatibility. New applications should use the operator gauss_filtergauss_filterGaussFiltergauss_filterGaussFilterGaussFilter instead.

Signature

Description

The operator gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage smoothes images using the discrete Gaussian. The smoothing effect increases with increasing filter size. The following filter sizes (SizeSizeSizeSizeSizesize) are supported (the sigma value of the gauss function is indicated in brackets):

    3    (0.65)
    5    (0.87)
    7    (1.43)
    9    (1.88)
    11   (2.31)

The operator binomial_filterbinomial_filterBinomialFilterbinomial_filterBinomialFilterBinomialFilter can be used as an alternative to gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage. binomial_filterbinomial_filterBinomialFilterbinomial_filterBinomialFilterBinomialFilter is significantly faster than gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage. It should be noted that the mask size in binomial_filterbinomial_filterBinomialFilterbinomial_filterBinomialFilterBinomialFilter does not lead to the same amount of smoothing as the mask size in gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage. Corresponding mask sizes can be determined based on the respective values of the Gaussian smoothing parameter sigma.

gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage can be executed on OpenCL devices for all supported image types. However, the OpenCL impelementation can produce slightly different results from the scalar implementation.

Attention

In order to be able to process gauss_imagegauss_imageGaussImagegauss_imageGaussImageGaussImage on on OpenCL device, ImageImageImageImageImageimage must be at least 64 pixels in both width and height.

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.

Parallelization

• 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

gauss_image(Input,Gauss,7)
regiongrowing(Gauss,Segments,7,7,5,100)

gauss_image(Input,&Gauss,7,);
regiongrowing(Gauss,&Segments,7,7,5,100,);

gauss_image(Input,Gauss,7)
regiongrowing(Gauss,Segments,7,7,5,100)

gauss_image(Input,Gauss,7)
regiongrowing(Gauss,Segments,7,7,5,100)

gauss_image(Input,Gauss,7)
regiongrowing(Gauss,Segments,7,7,5,100)

gauss_image(Input,Gauss,7)
regiongrowing(Gauss,Segments,7,7,5,100)

Complexity

For each pixel: O(Size * 2).

Result

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

Module

Foundation