gauss_filter — Smooth using discrete gauss functions.
The operator gauss_filter smoothes images using the discrete Gaussian, a discrete approximation of the Gaussian function,
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 (0.600) 5 (1.075) 7 (1.550) 9 (2.025) 11 (2.550)For border treatment the gray values of the images are reflected at the image borders. Notice that, contrary to the operator gauss_image, the relationship between the filter mask size and its respective value for the sigma parameter is linear.
The operator binomial_filter can be used as an alternative to gauss_filter. binomial_filter is significantly faster than gauss_filter. 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_filter. Corresponding mask sizes can be determined based on the respective values of the Gaussian smoothing parameter sigma.
gauss_filter 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_filter 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_filter 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