Hi Ross On 2015-04-10 13:03:57, Ross McKinney <ross.m.mckinney@gmail.com> wrote:

Does anyone know of a more efficient way to implement the skimage.transform.radon() function?

Beylkin's 1987 paper already describes a faster way of computing it; this 1993 paper improves further upon those ideas: http://dx.doi.org/10.1109/83.236530 Unfortunately, we do not have an implementation of that paper available.

I am trying to rotationally align a large series of images (>10,000) by taking their radon projections and then converting them into the frequency domain. Unfortunately, this is going to take a really long time using the current implementation of the radon() function. I've started to take a look at the code myself, but I'm not an expert on the subject. Also, if there are any alternative methods of rotational alignment (that are computationally efficient), I'd love to hear them!

Rotation correction can be done without the help of the radon transform. E.g., rotation can be estimated directly from the Fourier transform. The log-polar transform allows for estimates of rotation and scale. With offset, it becomes a bit more tricky but can still be done. Perhaps show us the kinds of images you have in mind? Regards Stéfan