Superresolution Reconstruction Through Object Modeling And Parameter Estimation

E. Mark Haacke; Zhi Pei Liang; Steven H. Izen

doi:10.1109/29.17545

Superresolution Reconstruction Through Object Modeling And Parameter Estimation

E. Mark Haacke, Zhi Pei Liang, Steven H. Izen

Research output: Contribution to journal › Article › peer-review

Abstract

Fourier transform reconstruction with limited data is often encountered in tomographic imaging problems. Conventional techniques, such as FFT-based methods, the spatial-support-limited extrapolation method, and the maximum entropy method, have not been optimal in terms of both Gibbs ringing reduction and resolution enhancement. In this correspondence, a new method based on object modeling and parameter estimation is proposed to achieve superresolution reconstruction.

Original language	English (US)
Pages (from-to)	592-595
Number of pages	4
Journal	IEEE Transactions on Acoustics, Speech, and Signal Processing
Volume	37
Issue number	4
DOIs	https://doi.org/10.1109/29.17545
State	Published - Apr 1989
Externally published	Yes

ASJC Scopus subject areas

Signal Processing

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title = "Superresolution Reconstruction Through Object Modeling And Parameter Estimation",

abstract = "Fourier transform reconstruction with limited data is often encountered in tomographic imaging problems. Conventional techniques, such as FFT-based methods, the spatial-support-limited extrapolation method, and the maximum entropy method, have not been optimal in terms of both Gibbs ringing reduction and resolution enhancement. In this correspondence, a new method based on object modeling and parameter estimation is proposed to achieve superresolution reconstruction.",

author = "{Mark Haacke}, E. and Liang, {Zhi Pei} and Izen, {Steven H.}",

year = "1989",

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doi = "10.1109/29.17545",

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AU - Liang, Zhi Pei

AU - Izen, Steven H.

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N2 - Fourier transform reconstruction with limited data is often encountered in tomographic imaging problems. Conventional techniques, such as FFT-based methods, the spatial-support-limited extrapolation method, and the maximum entropy method, have not been optimal in terms of both Gibbs ringing reduction and resolution enhancement. In this correspondence, a new method based on object modeling and parameter estimation is proposed to achieve superresolution reconstruction.

AB - Fourier transform reconstruction with limited data is often encountered in tomographic imaging problems. Conventional techniques, such as FFT-based methods, the spatial-support-limited extrapolation method, and the maximum entropy method, have not been optimal in terms of both Gibbs ringing reduction and resolution enhancement. In this correspondence, a new method based on object modeling and parameter estimation is proposed to achieve superresolution reconstruction.

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Superresolution Reconstruction Through Object Modeling And Parameter Estimation

Abstract

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