[NEW FEATURE] Parallelize filter_convolve

[zaccharieramzi]

Is your feature request related to a problem? Please describe.
I'm always frustrated when I run the filter_convolve function on big images (512 x 512), because it takes a lot of time.
Example: 412 ms (measured with %%timeit) for a starlet transform with 4 levels of decomposition (without the coarse scale).

Describe the solution you'd like
I would like to have the filter_convolve function parallelized. Indeed, each convolution could be run in its own thread or process.
I think using joblib, especially the embarrassingly parallel helper, could help us move forward in that direction.

Describe alternatives you've considered
I haven't consider any alternatives.

[zaccharieramzi]

The operations that we have at hand are too small to benefit greatly from parallelizing. I suggest dropping that idea.
The filter_convolve is now faster thanks to the trimming (see #50 ). I think the way to go to accelerate even further would be to use tensorflow, to leverage parallel convolution and sparse convolution, but this is I think a bit of a stretch right now.

I also tried convolve instead of fft_convolve because it should work better now that the filters are trimmed, but it didn't provide a significant improvement.