Polyphase back-projection filtering for image resolution enhancement

B. Cohen, I. Dinstein

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


The method for reconstruction and restoration of super-resolution images from sets of low-resolution images presented is an extension of the algorithm proposed by Irani and Peleg (1991). After estimating the projective transformation parameters between the image sequence frames, the observed data are transformed into a sequence with only quantized sub-pixel translations. The super-resolution reconstruction is an iterative process, in which a high-resolution image is initialized and iteratively improved. The improvement is achieved by back-projecting the errors between the translated low-resolution images and the respective images obtained by simulating the imaging system. The imaging system's point-spread function (PSF) and the back-projection function are first estimated with a resolution higher than that of the super-resolution image. The two functions are then decimated so that two banks of polyphase filters are obtained. The use of the polyphase filters allows exploitation of the input data without any smoothing and/or interpolation operations. The presented experimental results show that the resolution improvement is better than the results obtained with Irani and Peleg's algorithm.

Original languageEnglish
Pages (from-to)318-322
Number of pages5
JournalIEE Proceedings: Vision, Image and Signal Processing
Issue number4
StatePublished - 1 Aug 2000

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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