gauss_image — Smooth using discrete gauss functions.
The operator gauss_image smoothes images using the discrete Gaussian. The smoothing effect increases with increasing filter size. The following filter sizes (Size) 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)
For border treatment the gray values of the images are reflected at the image borders.
The operator binomial_filter can be used as an alternative to gauss_image. binomial_filter is significantly faster than gauss_image. It should be noted that the mask size in binomial_filter does not lead to the same amount of smoothing as the mask size in gauss_image. Corresponding mask sizes can be determined based on the respective values of the Gaussian smoothing parameter sigma.
gauss_image can be executed on OpenCL devices for all supported image types. However, the OpenCL impelementation can produce slightly different results from the scalar implementation.
In order to be able to process gauss_image on on OpenCL device, Image must be at least 64 pixels in both width and height.
Image to be smoothed.
Required filter size.
Default value: 5
List of values: 3, 5, 7, 9, 11
For each pixel: O(Size * 2).
If the parameter values are correct the operator gauss_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>). If necessary an exception is raised.
regiongrowing, threshold, sub_image, dyn_threshold, auto_threshold
binomial_filter, smooth_image, derivate_gauss, isotropic_diffusion
mean_image, anisotropic_diffusion, sigma_image, gen_lowpass