Real-time video super-resolution restruction based on GPU acceleration
CHEN Xiangji1,2,HAN Guoqiang2,ZHANG Zhiyuan1
1. College of Information, South China Agricultural University, Guangzhou Guangdong 510642, China 2. School of Computer Science and Engineering, South China University of Technology, Guangzhou Guangdong 510006, China
Abstract：The methods of image super-resolution via sparse representation achieve good quality image reconstruction, but the CPU-based implementation of the methods hardly satisfies the requirement of real-time video super-resolution because of high computational complexity. Then, the method of real-time video super-resolution via sparse representation based on GPU acceleration was proposed. It focused on optimizing data parallel processing and improving resource utilization of GPU, including utilizing queues for video sequences, improving memory concurrent access rates, employing Principal Component Analysis (PCA) dimensionality reduction and optimizing dictionary querying operation. As a result, compared with the CPU-based implementation, the speed of data processing is increased two orders of magnitude, and the speed of playing a video with the size of 669×546 reaches 33 frames per second.
2013, Vol. 33 
