Super-Resolution Reconstruction Using Wavelet Transform

Because of a deterioration in resolution, the distant parts of images taken by a camera are of an inferior quality. Super-resolution is one of the effective methods to improve the quality of low resolution images. In super-resolution, a high resolution-image is generated from multiple low resolution images by image processing such as inverse discrete wavelet transformation. Inverse discrete wavelet transform can expand the image by doubling the resolution. Super-resolution by inverse discrete wavelet transform needs three different high frequency components in the image to be improved. For accurate expansion by inverse discrete wavelet transform, these high frequency components must be accurate. However, it is difficult to estimate these components because of the sensitivity of the transform toward the margin of error. This is why there are few methods for improving images by using wavelet transform. Therefore, we have tried to reduce this domain to estimate. Estimation of high frequency components becomes easy, if we can improve low resolution images after the domain has been reduced. In this paper, we have tried to limit the domain of these high frequency components.


  • English

Media Info

  • Media Type: CD-ROM
  • Features: Figures; Photos; References;
  • Pagination: 12p
  • Monograph Title: ITS Connections: Saving Time. Saving Lives

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Filing Info

  • Accession Number: 01146681
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Dec 6 2009 5:59PM