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Super resolution reconstruction has been one of the most active research areas. The goal of Super-Resolution (SR) methods is to recover a high resolution image from one or more low resolution input images. Image resolution describes the details contained in an image, the higher the resolution, the more image details. The resolution of a digital image can be classified in many different ways: pixel resolution, spatial resolution, spectral resolution, temporal resolution, and radiometric resolution. Following are the techniques:

  • Image observation model
  • Super-resolution in the frequency domain
  • Interpolation-restoration: non-iterative approaches
  • Statistical approaches
  • Example-based approach
  • Set theoretic restoration

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