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 CPUbased 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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
