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Related Experiment Videos

Preconditioning for edge-preserving image super resolution.

Stéphane Pelletier1, Jeremy R Cooperstock

  • 1Department of Electrical and Computer Engineering, McGill University, Montréal, QC, Canada.

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
|June 23, 2011
PubMed
Summary
This summary is machine-generated.

We developed a new preconditioning method to speed up edge-preserving image super-resolution (SR). This technique efficiently updates the preconditioner, maintaining model optimality for integer and non-integer zoom factors.

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Area of Science:

  • Computer Vision
  • Image Processing
  • Numerical Analysis

Background:

  • Image super-resolution (SR) aims to enhance image detail.
  • Edge-preserving SR is crucial for maintaining image fidelity.
  • Accelerating SR solutions is vital for practical applications.

Purpose of the Study:

  • To propose a simple preconditioning method for accelerating edge-preserving image super-resolution (SR).
  • To address challenges posed by varying Hessians in edge-preserving SR.
  • To enable SR with rational magnification factors.

Main Methods:

  • Reordering high-resolution (HR) pixels similar to quadratic SR preconditioning.
  • Developing an efficient update scheme for the preconditioner to handle varying Hessians.
  • Adapting preconditioning for SR problems with rational magnification factors.

Main Results:

  • The proposed method accelerates the solution of edge-preserving SR problems.
  • The technique maintains the optimality of the observation model, unlike other methods.
  • Efficient preconditioning is achieved for SR with rational zoom factors using circulant operators.

Conclusions:

  • The developed preconditioning method offers an efficient way to accelerate edge-preserving SR.
  • This approach is robust for both integer and rational magnification factors.
  • The method preserves the accuracy of the SR observation model.