More advanced windows/Weighted windows

[irslushy]

Hello - I'm looking to extend the functionality of the mapwindow method a bit - in Python it's possible to not just specify dimensions of the window but rather an array of weights for the neighboring points and I'd love for there to be something similar in Julia. As far as I can tell this has not been implemented yet but just wanted to make sure I wasn't missing something before working on it. Anyone have any thoughts on this?

[mkitti]

In Julia, you can pass an arbitrary function as the first argument or via the do syntax. Within this function you can multiply the window by arbitrary weights as desired.

julia> using ImageFiltering

julia> img = zeros(10, 10)
10×10 Matrix{Float64}:
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0

julia> img[5,5] = img[6,6] = 1
1

julia> img
10×10 Matrix{Float64}:
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  1.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0  0.0

ulia> weights = reshape(1:9, 3, 3)
3×3 reshape(::UnitRange{Int64}, 3, 3) with eltype Int64:
 1  4  7
 2  5  8
 3  6  9

julia> mapwindow(I, (3,3)) do w
           sum(w .* weights)
       end
10×10 Matrix{Float64}:
 0.0  0.0  0.0  0.0   0.0   0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0   0.0   0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0   0.0   0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  9.0   6.0   3.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  8.0  23.0  14.0  6.0  0.0  0.0  0.0
 0.0  0.0  0.0  7.0  20.0  11.0  4.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0  14.0   8.0  2.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0   0.0   0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0   0.0   0.0  0.0  0.0  0.0  0.0
 0.0  0.0  0.0  0.0   0.0   0.0  0.0  0.0  0.0  0.0