PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network

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,...

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Main Authors: Mingzhu Shi, Shuaiqi Liu
Format: Article
Language:English
Published: Wiley 2015-10-01
Series:International Journal of Distributed Sensor Networks
Online Access:https://doi.org/10.1155/2015/758034
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author Mingzhu Shi
Shuaiqi Liu
author_facet Mingzhu Shi
Shuaiqi Liu
author_sort Mingzhu Shi
collection DOAJ
description 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.
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series International Journal of Distributed Sensor Networks
spelling doaj-art-edc0c9c8cead48aea25ee9c615102ff82025-08-20T03:20:43ZengWileyInternational Journal of Distributed Sensor Networks1550-14772015-10-011110.1155/2015/758034758034PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor NetworkMingzhu Shi0Shuaiqi Liu1 College of Electronic and Communication Engineering, Tianjin Normal University, Tianjin 300387, China College of Electronic and Information Engineering, Hebei University, Baoding 071000, ChinaIn 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.https://doi.org/10.1155/2015/758034
spellingShingle Mingzhu Shi
Shuaiqi Liu
PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network
International Journal of Distributed Sensor Networks
title PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network
title_full PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network
title_fullStr PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network
title_full_unstemmed PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network
title_short PSF Estimation via Gradient Cepstrum Analysis for Image Deblurring in Hybrid Sensor Network
title_sort psf estimation via gradient cepstrum analysis for image deblurring in hybrid sensor network
url https://doi.org/10.1155/2015/758034
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AT shuaiqiliu psfestimationviagradientcepstrumanalysisforimagedeblurringinhybridsensornetwork