Výsledky vyhledávání - generic blind deconvolution algorithms

  1. 1

    Blind atmospheric turbulence deconvolution Autor Deledalle, Charles-Alban, Gilles, Jérôme

    ISSN: 1751-9659, 1751-9667
    Vydáno: The Institution of Engineering and Technology 01.12.2020
    Vydáno v IET image processing (01.12.2020)
    “…A new blind image deconvolution technique is developed for atmospheric turbulence deblurring to overcome limitations of ‘generic…”
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    Journal Article
  2. 2

    Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution Autor Huang, Yunshi, Chouzenoux, Emilie, Pesquet, Jean-Christophe

    ISSN: 1057-7149, 1941-0042, 1941-0042
    Vydáno: United States IEEE 01.01.2023
    Vydáno v IEEE transactions on image processing (01.01.2023)
    “…In this paper, we introduce a variational Bayesian algorithm (VBA) for image blind deconvolution…”
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    Journal Article
  3. 3

    Blind Deconvolution Using Convex Programming Autor Ahmed, Ali, Recht, Benjamin, Romberg, Justin

    ISSN: 0018-9448, 1557-9654
    Vydáno: New York, NY IEEE 01.03.2014
    “…*. This observation allows us to recast the deconvolution problem as low-rank matrix recovery problem from linear measurements, whose natural convex relaxation is a nuclear norm minimization program…”
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    Journal Article
  4. 4

    Restoration of atmospheric turbulence degraded images Autor Shi, Dongfeng, Fan, Chengyu, Shen, Hong, Zhang, Pengfei, Qiao, Chunhong, Feng, Xiaoxing, Wang, Yingjian

    ISSN: 0030-4018, 1873-0310
    Vydáno: Elsevier B.V 01.12.2011
    Vydáno v Optics communications (01.12.2011)
    “…A blind image deconvolution algorithm in the frequency domain is proposed which uses the edge-preserving method and generic bandwidth of optical system…”
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    Journal Article
  5. 5

    Structured Local Optima in Sparse Blind Deconvolution Autor Zhang, Yuqian, Kuo, Han-Wen, Wright, John

    ISSN: 0018-9448, 1557-9654
    Vydáno: New York IEEE 01.01.2020
    “…Blind deconvolution is a ubiquitous problem aiming to recover a convolution kernel <inline-formula> <tex-math notation="LaTeX">\boldsymbol a_{0}\in \mathbb R ^{k} </tex-math></inline-formula…”
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    Journal Article
  6. 6

    Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution Autor Ma, Cong, Wang, Kaizheng, Chi, Yuejie, Chen, Yuxin

    ISSN: 1615-3375, 1615-3383
    Vydáno: New York Springer US 01.06.2020
    “…Recent years have seen a flurry of activities in designing provably efficient nonconvex procedures for solving statistical estimation problems. Due to the…”
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    Journal Article
  7. 7

    Fast and Guaranteed Blind Multichannel Deconvolution Under a Bilinear System Model Autor Lee, Kiryung, Tian, Ning, Romberg, Justin

    ISSN: 0018-9448, 1557-9654
    Vydáno: New York IEEE 01.07.2018
    “…We consider the multichannel blind deconvolution problem where we observe the output of multiple channels that are all excited with the same unknown input…”
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    Journal Article
  8. 8

    Unrolled Variational Bayesian Algorithm for Image Blind Deconvolution Autor Huang, Yunshi, Chouzenoux, Emilie, Jean-Christophe Pesquet

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 14.10.2021
    Vydáno v arXiv.org (14.10.2021)
    “…In this paper, we introduce a variational Bayesian algorithm (VBA) for image blind deconvolution…”
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    Paper
  9. 9

    Leveraging Diversity and Sparsity in Blind Deconvolution Autor Ahmed, Ali, Demanet, Laurent

    ISSN: 0018-9448, 1557-9654
    Vydáno: New York IEEE 01.06.2018
    “…This paper considers recovering <inline-formula> <tex-math notation="LaTeX">L </tex-math></inline-formula>-dimensional vectors <inline-formula> <tex-math…”
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    Journal Article
  10. 10

    Blind equalization of square-QAM signals: a multimodulus approach Autor Abrar, Shafayat, Nandi, Asoke

    ISSN: 0090-6778, 1558-0857
    Vydáno: New York IEEE 01.06.2010
    Vydáno v IEEE transactions on communications (01.06.2010)
    “…By generalizing and modifying some existing cost-functions, we present two new, generic and efficient multimodulus families of blind equalization algorithms for use in higher-order quadrature…”
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    Journal Article
  11. 11

    Optimal sparse representations for blind source separation and blind deconvolution: a learning approach Autor Bronstein, M.M., Bronstein, A.M., Zibulevsky, M., Zeevi, Y.Y.

    ISBN: 0780385543, 9780780385542
    ISSN: 1522-4880
    Vydáno: Piscataway NJ IEEE 2004
    “…We present a generic approach, which allows to adapt sparse blind deconvolution and blind source separation algorithms to arbitrary sources…”
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    Konferenční příspěvek
  12. 12

    On the Convergence of Learning-Based Iterative Methods for Nonconvex Inverse Problems Autor Liu, Risheng, Cheng, Shichao, He, Yi, Fan, Xin, Lin, Zhouchen, Luo, Zhongxuan

    ISSN: 0162-8828, 1939-3539, 2160-9292, 1939-3539
    Vydáno: United States IEEE 01.12.2020
    “… This paper moves beyond these limits and proposes Flexible Iterative Modularization Algorithm (FIMA…”
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    Journal Article
  13. 13

    Closed-Loop Restoration Approach to Blurry Images Based on Machine Learning and Feedback Optimization Autor Yousaf, Saqib, Qin, Shiyin

    ISSN: 1057-7149, 1941-0042, 1941-0042
    Vydáno: United States IEEE 01.12.2015
    Vydáno v IEEE transactions on image processing (01.12.2015)
    “…Blind image deconvolution (BID) aims to remove or reduce the degradations that have occurred during the acquisition or processing…”
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    Journal Article
  14. 14

    A fast linear programming algorithm for blind equalization Autor Ding, Zhi, Zhi-Quan Luo

    ISSN: 0090-6778, 1558-0857
    Vydáno: New York IEEE 01.09.2000
    Vydáno v IEEE transactions on communications (01.09.2000)
    “… For a generic class of channels with persistently exciting quadrature amplitude modulation input signals, this new algorithm allows the convergence of equalizer parameters to a unique global minimum…”
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    Journal Article
  15. 15

    Learning Discriminative Data Fitting Functions for Blind Image Deblurring Autor Jinshan Pan, Jiangxin Dong, Yu-Wing Tai, Zhixun Su, Ming-Hsuan Yang

    ISSN: 2380-7504
    Vydáno: IEEE 01.10.2017
    “… While existing algorithms mainly focus on developing image priors for blur kernel estimation and non-blind deconvolution, only a few methods consider the effect of data fitting functions…”
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    Konferenční příspěvek
  16. 16

    Blind Bi-Level Image Restoration With Iterated Quadratic Programming Autor Lam, E.Y.

    ISSN: 1549-7747, 1558-3791
    Vydáno: New York IEEE 01.01.2007
    “… While image restoration has been applied frequently in such cases, many of these algorithms do not explicitly incorporate knowledge of a bi-level object, but attempt to apply a generic restoration…”
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    Journal Article
  17. 17

    On the causality problem in time-domain blind source separation and deconvolution algorithms Autor Aichner, R., Buchner, H., Kellermann, W.

    ISBN: 9780780388741, 0780388747
    ISSN: 1520-6149
    Vydáno: IEEE 2005
    “…Using a recently presented generic framework for multichannel blind signal processing for convolutive mixtures, we investigate the problem of incorporating acausal delays which are necessary…”
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    Konferenční příspěvek
  18. 18

    Efficient Methodologies for Single-Image Blind Deconvolution and Deblurring Autor Khan, Aftab

    ISBN: 9798297943438
    Vydáno: ProQuest Dissertations & Theses 01.01.2014
    “…The Blind Image Deconvolution/Deblurring (BID) problem was realised in the early 1960s but it still remains a challenging task for the image processing research…”
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    Dissertation
  19. 19

    Relationships between the constant modulus and Wiener receivers Autor Zeng, H.H., Lang Tong, Johnson, C.R.

    ISSN: 0018-9448, 1557-9654
    Vydáno: New York IEEE 01.07.1998
    “…The Godard (1980) or the constant modulus algorithm (CMA) is an effective technique for blind receiver design in communications…”
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    Journal Article
  20. 20

    Implicit Regularization in Nonconvex Statistical Estimation: Gradient Descent Converges Linearly for Phase Retrieval, Matrix Completion, and Blind Deconvolution Autor Ma, Cong, Wang, Kaizheng, Chi, Yuejie, Chen, Yuxin

    ISSN: 2331-8422
    Vydáno: Ithaca Cornell University Library, arXiv.org 30.07.2019
    Vydáno v arXiv.org (30.07.2019)
    “…Recent years have seen a flurry of activities in designing provably efficient nonconvex procedures for solving statistical estimation problems. Due to the…”
    Získat plný text
    Paper