document the performance caveat on abstract eltype

Gray.(img) is used widely tha Array{Gray, 2}(undef, sz...) or zeros(Gray, sz) becomes very alluring. However, there's a significant performance gap here:

julia> @btime zeros(Gray, 100, 100);
  39.331 μs (10002 allocations: 234.45 KiB)

julia> @btime zeros(Gray{N0f8}, 100, 100);
  2.565 μs (1 allocation: 9.94 KiB)

julia> @btime Array{Gray, 2}(undef, 100, 100);
  1.841 μs (2 allocations: 78.20 KiB)

julia> @btime Array{Gray{N0f8}, 2}(undef, 100, 100);
  127.157 ns (1 allocation: 9.94 KiB)

This is probably a JuliaImages specific confusion, because when we write Array{AbstractFloat, 2} we know it's an abstract type. But for Gray it's very likely that users don't get this.

Ref: https://docs.julialang.org/en/v1/manual/performance-tips/#man-performance-abstract-container-1

Start with the Julia performance-tips section linked in the issue and review the existing JuliaImages documentation for discussion of Gray and array construction. Document that abstract Gray containers can be substantially slower than concrete Gray{N0f8} containers, using the reported examples as context. Done means the caveat and the distinction between Gray and Gray{N0f8} are clearly explained in the appropriate documentation.