Parallel image processing with CUDA and OpenGL

The motivation of our work is to demonstrate the interest of the GPU exploitation using CUDA and OpenGL for boosting performances of image processing algorithms. This concern is particularly important for a broad set of applications, such as real-time video processing, motion analysis, etc. We have implemented several algorithms such as geometrical transformations, removing noise, Gaussian smoothing, edge detection. These algorithms have been applied on high resolution and medical images. We propose a development scheme based upon CUDA for parallel constructs and OpenGL for visualization, which reduces data transfer between device and host memories. Experimental results have been conducted on several platforms, e.g. GPU GeForce8600 and GPU GTX280, showing a global speedup ranging from 20 to 60, by comparison with a standard CPU implementation.