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GPU-based parallel algorithm for blind image restoration using midfrequency-based methods
Xie, Lang; Luo, Yi-Han; Bao, Qi-Liang
Volume8910
Pages89101R
2013
Language英语
ISSN0277786X
DOI10.1117/12.2034733
Indexed ByEi
Subtype会议论文
AbstractGPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images. © 2013 SPIE.; GPU-based general-purpose computing is a new branch of modern parallel computing, so the study of parallel algorithms specially designed for GPU hardware architecture is of great significance. In order to solve the problem of high computational complexity and poor real-time performance in blind image restoration, the midfrequency-based algorithm for blind image restoration was analyzed and improved in this paper. Furthermore, a midfrequency-based filtering method is also used to restore the image hardly with any recursion or iteration. Combining the algorithm with data intensiveness, data parallel computing and GPU execution model of single instruction and multiple threads, a new parallel midfrequency-based algorithm for blind image restoration is proposed in this paper, which is suitable for stream computing of GPU. In this algorithm, the GPU is utilized to accelerate the estimation of class-G point spread functions and midfrequency-based filtering. Aiming at better management of the GPU threads, the threads in a grid are scheduled according to the decomposition of the filtering data in frequency domain after the optimization of data access and the communication between the host and the device. The kernel parallelism structure is determined by the decomposition of the filtering data to ensure the transmission rate to get around the memory bandwidth limitation. The results show that, with the new algorithm, the operational speed is significantly increased and the real-time performance of image restoration is effectively improved, especially for high-resolution images. © 2013 SPIE.
Conference NameProceedings of SPIE: International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications
Conference Date2013
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Document Type会议论文
Identifierhttp://ir.ioe.ac.cn/handle/181551/7401
Collection光电工程总体研究室(一室)
Affiliation Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China
Recommended Citation
GB/T 7714
Xie, Lang,Luo, Yi-Han,Bao, Qi-Liang. GPU-based parallel algorithm for blind image restoration using midfrequency-based methods[C],2013:89101R.
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