But I will definitely post some benchmarking results soon, as they are crucial for the optimization stage.
By the way, any suggestions/contributions to the project are more than welcome!
All of the blur/ functions could see big improvements with some simple changes:
* Use separable kernels whenever possible (this reduces a O(K^2) evaluation to 2K evaluations)
Some filters (like your box filter) can be done efficiently as a linear combination of IID filters (i.e. implicitly computing a pair of running sums, subtracting one from the other as you go).
* The convolve/ package could use some cache blocking, and should definitely have the conditionals on the inner-loop removed.
Unfortunately, these changes will likely make your code a bit more difficult to read.
This is one of the reasons Halide has become so popular for image-processing (if you're interested in high performance image processing without sacrificing maintainability, Halide is definitely worth looking into!)
Halide looks very interesting, I found the "Halide Talk" video on their website to be a great primer on their methods.