CUDA vs FPGA for Image Processing; which is better Is there anyone with Image Processing background who can suggests which one is better for Image Processing algorithms among CUDA and FPGA. I'm specifically looking to write code for Wavelet Transform and Discrete Cosine Transform and eventually writing code for Quantization and Arithmatic coding, but i am confused which hardware programming language should i focus on among CUDA and FPGA.

Here are few questions i want to ask,


Which one is better for Image Processing like compression, watermarking etc ? 
Which one is Faster ?
Which one is easy to    implement ?
Did you have a chance to look at Spiral site?  They try to address this question.  For example, there are special cases where FPGA will run O(N) instead of the customary O(N log N).

Here's a paper that deals with generating FPGA.

All the way at the end of benchmarks page they show performance of a software algorithm enhanced with FPGA-based solvers.

P.S.  It's worth noting that Spiral can be used to optimize algorithms other than FFT, but presented data outlines the popular case only.