GPU Based Real-Time Enhancement of High Resolution Image

Curvature filter and gradient transform based image enhancement algorithm can effectively suppress noises and enhance image edges. However, it is very hard to be carried out in real time due to the large computing load. To address this problem, a GPU based parallel implementation is proposed in this paper. First, aiming at the characteristics of the algorithm, a numerical implementation method based on central-difference is proposed. Then a domain decomposition scheme is utilized in parallel Gaussian curvature filter to remove the dependence of neighboring pixels and guarantee convergence. Finally, we make the multiprocessor wrap occupancy reach 100% by optimizing the thread grid and register usage. Experimental results demonstrate that our parallel method runs 200-300 times faster than CPU serial method with real time processing of 4096x4096 resolution image, which indicates a great potential for application.