Convolutional Sparse Coding for Image Super-Resolution

@article{Gu2015ConvolutionalSC,
  title={Convolutional Sparse Coding for Image Super-Resolution},
  author={Shuhang Gu and Wangmeng Zuo and Qi Xie and Deyu Meng and Xiangchu Feng and Lei Zhang},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={1823-1831}
}
Most of the previous sparse coding (SC) based super resolution (SR) methods partition the image into overlapped patches, and process each patch separately. These methods, however, ignore the consistency of pixels in overlapped patches, which is a strong constraint for image reconstruction. In this paper, we propose a convolutional sparse coding (CSC) based SR (CSC-SR) method to address the consistency issue. Our CSC-SR involves three groups of parameters to be learned: (i) a set of filters to… CONTINUE READING

Similar Papers

Citations

Publications citing this paper.
SHOWING 1-10 OF 108 CITATIONS, ESTIMATED 97% COVERAGE

Resolution-Aware Network for Image Super-Resolution

  • IEEE Transactions on Circuits and Systems for Video Technology
  • 2019
VIEW 9 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Joint Face Hallucination and Deblurring via Structure Generation and Detail Enhancement

  • International Journal of Computer Vision
  • 2018
VIEW 5 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

Convolutional Dictionary Learning

VIEW 5 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

Convolutional Dictionary Learning: A Comparative Review and New Algorithms

  • IEEE Transactions on Computational Imaging
  • 2017
VIEW 4 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

Simultaneous Super-Resolution and Cross-Modality Synthesis of 3D Medical Images Using Weakly-Supervised Joint Convolutional Sparse Coding

  • 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2017
VIEW 4 EXCERPTS
CITES METHODS
HIGHLY INFLUENCED

Wavelet-based single image super-resolution with an overall enhancement procedure

  • 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2017
VIEW 8 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

End-to-End Image Super-Resolution via Deep and Shallow Convolutional Networks

VIEW 8 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

FILTER CITATIONS BY YEAR

2016
2019

CITATION STATISTICS

  • 10 Highly Influenced Citations

  • Averaged 31 Citations per year from 2017 through 2019

References

Publications referenced by this paper.
SHOWING 1-10 OF 37 REFERENCES

Efficient convolutional sparse coding

  • 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
  • 2014
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Image super-resolution as sparse representation of raw image patches

  • 2008 IEEE Conference on Computer Vision and Pattern Recognition
  • 2008
VIEW 17 EXCERPTS
HIGHLY INFLUENTIAL

Single Image Super-resolution Using Deformable Patches

  • 2014 IEEE Conference on Computer Vision and Pattern Recognition
  • 2014
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Anchored Neighborhood Regression for Fast Example-Based Super-Resolution

  • 2013 IEEE International Conference on Computer Vision
  • 2013
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

Beta Process Joint Dictionary Learning for Coupled Feature Spaces with Application to Single Image Super-Resolution

  • 2013 IEEE Conference on Computer Vision and Pattern Recognition
  • 2013
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

On Single Image Scale-Up Using Sparse-Representations

  • Curves and Surfaces
  • 2010
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

Super-resolution through neighbor embedding

  • Proceedings of the 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2004. CVPR 2004.
  • 2004
VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL