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I have an array which I want to filter using a Gaussian filter, similarly to scipy.ndimage.filter.gaussian_filter1d in Python.
What package would work best for this, and how would I use it?
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1. Gaussian Filtering. Gaussian filtering is used to blur images and remove noise and detail. g.
The Gaussian smoothing operator is a 2-D convolution operator that is used to `blur' images and remove detail and noise. In this sense it is similar to the mean filter, but it uses a different kernel that represents the shape of a Gaussian (`bell-shaped') hump.
Gaussian Filtering is widely used in the field of image processing. It is used to reduce the noise of an image. In this article we will generate a 2D Gaussian Kernel. The 2D Gaussian Kernel follows the below given Gaussian Distribution.
In Julia, the ImageFiltering.jl package can help you do this.
You can construct a 1D Gaussian kernel by ker = ImageFiltering.Kernel.gaussian((3,)) (the tuple is passed to represent the dimension of the desired output).
Then, if you have an array of data in data, you can perform the filtering operation by:
newdata = imfilter(data, ker)
If you want to do in-place filtering, there is also imfilter!.
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In addition to Kernel.gaussian((σ,)), there is also KernelFactors.IIRGaussian((σ,)),
which constructs an infinite-impulse response approximation to the Gaussian. This can be useful for very fast approximate-Gaussian filtering when σ is fairly large.
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