Multimedia Tools and Applications

, Volume 77, Issue 7, pp 7883–7907 | Cite as

Bidirectionally aligned sparse representation for single image super-resolution

  • Chao Xie
  • Weili Zeng
  • Shengqin Jiang
  • Xiaobo Lu


It has been demonstrated that the sparse representation based framework is one of the most popular and promising ways to handle the single image super-resolution (SISR) issue. However, due to the complexity of image degradation and inevitable existence of noise, the coding coefficients produced by imposing sparse prior only are not precise enough for faithful reconstructions. In order to overcome it, we present an improved SISR reconstruction method based on the proposed bidirectionally aligned sparse representation (BASR) model. In our model, the bidirectional similarities are first modeled and constructed to form a complementary pair of regularization terms. The raw sparse coefficients are additionally aligned to this pair of standards to restrain sparse coding noise and therefore result in better recoveries. On the basis of fast iterative shrinkage-thresholding algorithm, a well-designed mathematic implementation is introduced for solving the proposed BASR model efficiently. Thorough experimental results indicate that the proposed method performs effectively and efficiently, and outperforms many recently published baselines in terms of both objective evaluation and visual fidelity.


Single image super-resolution Sparse representation Sparse coefficient alignment Bidirectional similarities 



The authors would like to thank the associate editor and anonymous reviewers for their constructive and precious comments, which helped us a lot in improving the presentation of this work.

This work was supported by the National Natural Science Foundation of China (No.61374194, No.61403081), the National Key Science & Technology Pillar Program of China (No.2014BAG01B03), the Key Research and Development Program of Jiangsu Province (No. BE2016739), and a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Chao Xie
    • 1
    • 2
  • Weili Zeng
    • 3
  • Shengqin Jiang
    • 1
    • 2
  • Xiaobo Lu
    • 1
    • 2
  1. 1.School of AutomationSoutheast UniversityNanjing 210096China
  2. 2.Key Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of EducationNanjing 210096China
  3. 3.College of Civil AviationNanjing University of Aeronautics and AstronauticsNanjing 210016China

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