Develop - Faster implementation of DFT filter kernels

Changes were made to ```Image.applyGaussianFilter``` and ```Image.applyButterworthFilter``` preserving the current functionality but improving the performance of filter kernel creation, see this issue: [Image Filters are Slow](https://github.com/ingenuitas/SimpleCV/issues/346).  However, since the ```Image.applyDFTFilter``` takes up most of the computation time,  the performance gain on the overall function is about 7% (32.1 ms) (using ```img = Image("lenna");timeit img.applyGaussianFilter()``` on Intel® Core™ i7-3770K CPU @ 3.50GHz × 8 ), but gains may be more significant for higher resolution filters (>64x64)  and on slower systems.  Additionally, the code has been factored to allow for more advanced functionality to be added more simply in the future.