Image processing research areas using GPU
I've done a bit of GPGPU (for optical flow) during my PhD, so here are a few hints to help you:


choose a computation intensive task. You're very likely to find them in variational inverse problems (especially when expressed images instead of sparse feature sets). They are very common tasks: image deconvolution, compressed sensing, dense optical flow (and more broadly dense image registration...), dense 3D reconstruction, image segmentation... ;
from my point of view, non-local image denoising (using non-local means) is very easy to understand, and it's computation-intensive enough to have been included in NVidia's Cuda examples for quite a while. It really deserves a new, better GPU implementation (such as the GPU-based kd-trees proposed a few years ago). However, it may prove challenging for an undergrad;
a useful site to see what Image Processing tasks can be done on GPUs: the Austrian (T.U. Graz) lab GPU4Vision.