Abstract:

For the shortcoming of guided filtering, such as slow operational speed and non-real time processing,the algorithm is speeded up based on CUDA(Compute Unified Device Architecture). In the proposed method,the sum of neighbor pixels-value is calculated based on CUDA parallel programming, and the mean value is calculated. The key parameters of guided filtering are obtained by taking advantage of texture memory and registers and algorithm optimizing. The whole optimum of approach is achieved. Experimental results show that, compared with CPU-based guided filtering algorithm, the proposed CUDA-based algorithm is greatly speeded up and basically meets the requirement of real-time processing.

Key words: guided filtering, compute unified device architecture ( CUDA ), parallel processing, optimization technique