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Proceedings Paper

GPU-based parallel algorithm for blind image restoration using midfrequency-based methods
Author(s): Lang Xie; Yi-han Luo; Qi-liang Bao
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Paper Abstract

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.

Paper Details

Date Published: 30 August 2013
PDF: 10 pages
Proc. SPIE 8910, International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications, 89101R (30 August 2013); doi: 10.1117/12.2034733
Show Author Affiliations
Lang Xie, Institute of Optics and Electronics (China)
Yi-han Luo, Institute of Optics and Electronics (China)
Qi-liang Bao, Institute of Optics and Electronics (China)


Published in SPIE Proceedings Vol. 8910:
International Symposium on Photoelectronic Detection and Imaging 2013: Imaging Spectrometer Technologies and Applications
Lifu Zhang; Jianfeng Yang, Editor(s)

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