A Windowed-Total-Variation Regularization Constraint Model for Blind Image Restoration

Ganghua Liu; Wei Tian; Yushun Luo; Juncheng Zou; Shu Tang

doi:10.3745/JIPS.04.0233

논문KCI 등재

A Windowed-Total-Variation Regularization Constraint Model for Blind Image Restoration

Ganghua Liu|Wei Tian|Yushun Luo|Juncheng Zou|Shu Tang

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키워드

Edge Amplitude Image Restoration Kernel Spatial Scale Windowed-Total-Variation

초록

Blind restoration for motion-blurred images is always the research hotspot, and the key for the blind restorationis the accurate blur kernel (BK) estimation. Therefore, to achieve high-quality blind image restoration, thisthesis presents a novel windowed-total-variation method. The proposed method is based on the spatial scale ofedges but not amplitude, and the proposed method thus can extract useful image edges for accurate BKestimation, and then recover high-quality clear images. A large number of experiments prove the superiority.

Abstract

Blind restoration for motion-blurred images is always the research hotspot, and the key for the blind restorationis the accurate blur kernel (BK) estimation. Therefore, to achieve high-quality blind image restoration, thisthesis presents a novel windowed-total-variation method. The proposed method is based on the spatial scale ofedges but not amplitude, and the proposed method thus can extract useful image edges for accurate BKestimation, and then recover high-quality clear images. A large number of experiments prove the superiority.

참고문헌 (24)

Q. Shan, "High-quality motion deblurring from a single image", ACM Transactions on Graphics, 27(3), pp.1~10 (2018)
M. S. Almeida, "Blind and semi-blind deblurring of natural images", IEEE Transactions on Image Processing, 19(1), pp.36~52 (2010)
D. Krishnan, "Blind deconvolution using a normalized sparsity measure", Proceedings of the 24th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.233~240 (2011)
L. Xu, "Unnatural l0 sparse representation for natural image deblurring", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.1107~1114 (2013)
Z. Ma, "Handling motion blur in multi-frame super-resolution", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.5224~5232 (2015)
W. Zuo, "Learning iteration-wise generalized shrinkage–thresholding operators for blind deconvolution", IEEE Transactions on Image Processing, 25(4), pp.1751~1764 (2016)
J. Pan, "Blind image deblurring using dark channel prior", Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.1628~1636 (2016)
J. Pan, "L0-regularized intensity and gradient prior for deblurring text images and beyond", IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(2), pp.342~355 (2017)
Y. Guo, "Image blind deblurring using an adaptive patch prior", Tsinghua Science and Technology, 24(2), pp.238~248 (2019)
X. Chen, "Hyper-Laplacian regularized non-local low-rank prior for blind image deblurring", IEEE Access, 8, pp.136917~136929 (2020)
L. Chen, "Blind image deblurring with local maximum gradient prior", Proceedings of the IEEE, 2019, 1742~1750
H. Lim, "Texture-aware deblurring for remote sensing images using L0-based deblurring and L2-based fusion", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13, pp.3094~3108 (2020)
J. Cai, "Dark and bright channel prior embedded network for dynamic scene deblurring", IEEE Transactions on Image Processing, 29, pp.6885~6897 (2020)
J. Wu, "DAVID : dual-attentional video deblurring", Proceedings of the IEEE, 2020, 2376~2385
K. Zhang, "Deblurring by realistic blurring", Proceedings of the IEEE, 2020, 2734~2743
A. Li, "Deep image quality assessment driven single image deblurring", Proceedings of 2020 IEEE International Conference on Multimedia and Expo (ICME), pp.1~6 (2020)
Wenqi Ren, "Deblurring Dynamic Scenes via Spatially Varying Recurrent Neural Networks", IEEE Transactions on Pattern Analysis and Machine Intelligence, pp.1~1 (2021), Institute of Electrical and Electronics Engineers (IEEE)[DOI]
D. Ren, "Simultaneous fidelity and regularization learning for image restoration", IEEE Transactions on Pattern Analysis and Machine Intelligence, 43(1), pp.284~299 (2021)
Y. Hu, "Channel-wise and spatial feature modulation network for single image super-resolution", IEEE Transactions on Circuits and Systems for Video Technology, 30(11), pp.3911~3927 (2020)
B. Lu, "UID-GAN : unsupervised image deblurring via disentangled representations", IEEE Transactions on Biometrics, Behavior, and Identity Science, 2(1), pp.26~39 (2020)
Li Xu, "Structure extraction from texture via relative total variation", ACM Transactions on Graphics, 31(6), pp.1~10 (2012), Association for Computing Machinery (ACM)[DOI]
A. Levin, "Understanding and evaluating blind deconvolution algorithms", Proceedings of 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.1964~1971 (2009)
R. Kohler, "Recording and playback of camera shake:benchmarking blind deconvolution with a real-world database", Computer Vision – ECCV 2012, pp.27~40 (2012)
L. Sun, "Edge-based blur kernel estimation using patch priors", Proceedings of IEEE International Conference on Computational Photography (ICCP), pp.1~8 (2013)

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