Blind super-resolution using a learning-based approach

被引：38
|
作者：
Bégin, I [1 ]
Ferrie, FP [1 ]
机构：
[1] McGill Univ, Ctr Intelligent Machines, Montreal, PQ, Canada
来源：
PROCEEDINGS OF THE 17TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL 2 | 2004年
关键词：
D O I：
10.1109/ICPR.2004.1334046
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The super-resolution of a single image of unknown point-spread-function (PSF) is addressed by extending a learning framework using blind deconvolution with an uncertainty around the resulting PSF. Results indicate success in refining the estimate of the PSF as well as to restoring the image. A novel disparity measure is also proposed to quantify the results.
引用
收藏
页码：85 / 89
页数：5
相关论文
共 50 条
  • [21] Meta-learning based blind image super-resolution approach to different degradations
    Yang, Zhixiong
    Xia, Jingyuan
    Li, Shengxi
    Liu, Wende
    Zhi, Shuaifeng
    Zhang, Shuanghui
    Liu, Li
    Fu, Yaowen
    Guenduez, Deniz
    NEURAL NETWORKS, 2024, 178
  • [22] Image Super-Resolution Using DWT Based Learning with Zooming Approach
    Doshi, Meera D.
    Gajjar, Prakash P.
    Kothari, Ashish M.
    2018 5TH INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING AND INTEGRATED NETWORKS (SPIN), 2018, : 486 - 491
  • [23] Combining Exemplar-based Approach and learning-based Approach for Light Field Super-resolution Using a Hybrid Imaging System
    Zheng, Haitian
    Guo, Minghao
    Wang, Haoqian
    Liu, Yebin
    Fang, Lu
    2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOPS (ICCVW 2017), 2017, : 2481 - 2486
  • [24] Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline
    Qian, Guocheng
    Wang, Yuanhao
    Gu, Jinjin
    Dong, Chao
    Heidrich, Wolfgang
    Ghanem, Bernard
    Ren, Jimmy S.
    2022 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL PHOTOGRAPHY (ICCP), 2022,
  • [25] Volumetric Isosurface Rendering with Deep Learning-Based Super-Resolution
    Weiss, Sebastian
    Chu, Mengyu
    Thuerey, Nils
    Westermann, Rudiger
    IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, 2021, 27 (06) : 3064 - 3078
  • [26] Deep learning-based super-resolution in coherent imaging systems
    Liu, Tairan
    de Haan, Kevin
    Rivenson, Yair
    Wei, Zhensong
    Zeng, Xin
    Zhang, Yibo
    Ozcan, Aydogan
    SCIENTIFIC REPORTS, 2019, 9 (1)
  • [27] Training database adequacy analysis for learning-based super-resolution
    Begin, Isabelle
    Ferrie, Frank P.
    FOURTH CANADIAN CONFERENCE ON COMPUTER AND ROBOT VISION, PROCEEDINGS, 2007, : 29 - +
  • [28] A learning-based view extrapolation method for axial super-resolution
    Xiao, Zhaolin
    Shi, Jinglei
    Jiang, Xiaoran
    Guillemot, Christine
    NEUROCOMPUTING, 2021, 455 : 229 - 241
  • [29] Dictionary learning-based image super-resolution for multimedia devices
    Patel, Rutul
    Thakar, Vishvjit
    Joshi, Rutvij
    MULTIMEDIA TOOLS AND APPLICATIONS, 2023, 82 (11) : 17243 - 17262
  • [30] Learning-based super-resolution via canonical correlation analysis
    Wang, Yanzi
    Fan, Jiulun
    Xu, Jian
    Wu, Xiaomin
    International Journal of Signal Processing, Image Processing and Pattern Recognition, 2015, 8 (06) : 69 - 84
12345