NDLI: Non-iterative blind deconvolution algorithm based on power-law distribution

Content Provider	IET Digital Library
Author	Gao, Weizhe Xu, Xuebin Yang, Yikang Zhang, Zhiguang
Abstract	The spectral amplitude of most natural images is approximately isotropic and follows the power law. In this study, the authors propose a new non-iterative blind image deconvolution algorithm that builds an isosceles curve model to approximate the spectrum amplitude of the real image. In the authors’ proposed algorithm, the optical transfer function (OTF) is obtained by comparing the reconstructed and degraded spectra. Then they employ the integrated multidirectional comprehensive estimation to reduce the OTF estimation error. The restored image is then obtained by applying the estimated OTF and the Wiener filter. Experiments on image deconvolution tasks indicate that the proposed algorithm provides a significant performance gain by obtaining an accurate OTF, reducing ringing artefacts compared with existing algorithms, and realising real-time image restoration.
Starting Page	4499
Ending Page	4506
Page Count	8
ISSN	17519659
Volume Number	14
e-ISSN	17519667
Issue Number	Issue 17, Dec (2020)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2020.0647
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/14/17
Journal	IET Image Processing
Publisher Date	2020-12-07
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Approximation Theory Blind Deconvolution Algorithm Computer Vision And Image Processing Technique Curve Model Deconvolution Estimated OTF Filtering Method in Signal Processing Image Deconvolution Task Image Restoration Integrated Multidirectional Comprehensive Estimation Interpolation And Function Approximation Natural Image Noniterative Blind Image Deconvolution Algorithm Numerical Analysis Optical Transfer Function Optical, Image And Video Signal Processing OTF Estimation Error Power-law Distribution Real-time Image Restoration Spectral Amplitude Spectrum Amplitude Wiener Filter
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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