期刊名称：International Journal of Distributed Sensor Networks
印刷版ISSN：1550-1329
电子版ISSN：1550-1477
出版年度：2015
卷号：2015
DOI：10.1155/2015/758034
出版社：Hindawi Publishing Corporation
摘要：In hybrid sensor networks, information fusion from heterogeneous sensors is important, but quite often information such as image is blurred. Single image deblurring is a highly ill-posed problem and usually regularized by alternating estimating point spread function (PSF) and recovering blur image, which leads to high complexity and low efficiency. In this paper, we first propose an efficient PSF estimation algorithm based on gradient cepstrum analysis (GCA). Then, to verify the accuracy of the strategy, estimated PSFs are used for image deconvolution step, which exploits a novel total variation model coupling with a gradient fidelity term. We also adopt an alternating direction method (ADM) numerical algorithm with rapid convergence and high robustness to optimize the energy function. Both synthetic and real blur experiments show that our scheme can estimate PSF rapidly and produce comparable results without involving long time consuming.
