A parametric technique for superresolution image reconstruction

Yoram Bresler, Scott P. Litke

Research output: Contribution to journalConference articlepeer-review


A model-based approach for superresolution signal reconstruction from noisy bandlimited Fourier data is proposed. The approach combines the virtues of parametric and nonparametric techniques by maximum-likelihood fitting of the data by a mixture of exponentials and smooth basis functions. Performance bounds are derived and analyzed, and a model computationally efficient algorithm is described. The performance of the algorithm in simulations closely matches the bounds over a wide range of operating conditions. Overall, the reconstructions are far superior to those obtained by traditional Fourier transform processing.

Original languageEnglish (US)
Pages (from-to)1205-1208
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
StatePublished - 1990
Event1990 International Conference on Acoustics, Speech, and Signal Processing: Speech Processing 2, VLSI, Audio and Electroacoustics Part 2 (of 5) - Albuquerque, New Mexico, USA
Duration: Apr 3 1990Apr 6 1990

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


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