Two-dimensional cubic convolution for one-pass image restoration and reconstruction

Stephen E. Reichenbach; Jiazheng Shi

Two-dimensional cubic convolution for one-pass image restoration and reconstruction

Stephen E. Reichenbach, Jiazheng Shi

Computer Science and Engineering

Research output: Contribution to conference › Paper › peer-review

5 Scopus citations

Abstract

This paper formulates two-dimensional parametric cubic convolution for one-pass image restoration and reconstruction and derives a closed-form solution for the mean-square optimal parameters. The approach improves on traditional separable cubic convolution and relaxes the interpolation constraint to support restoration. The resulting kernel has five parameters and is designated 2D-5PCC-R. The closed-form solution for the optimal parameters is based on a continuous-discrete-continuous system model that accounts for the scene ensemble, acquisition blurring, sampling, noise, and processing. The analysis of the model leads to a simultaneous solution for five linear equations in the five parameters.

Original language	English (US)
Pages	2074-2076a
State	Published - 2004
Event	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004 - Anchorage, AK, United States Duration: Sep 20 2004 → Sep 24 2004

Conference

Conference	2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004
Country/Territory	United States
City	Anchorage, AK
Period	9/20/04 → 9/24/04

ASJC Scopus subject areas

Computer Science Applications
General Earth and Planetary Sciences

Cite this

Two-dimensional cubic convolution for one-pass image restoration and reconstruction. / Reichenbach, Stephen E.; Shi, Jiazheng.
2004. 2074-2076a Paper presented at 2004 IEEE International Geoscience and Remote Sensing Symposium Proceedings: Science for Society: Exploring and Managing a Changing Planet. IGARSS 2004, Anchorage, AK, United States.

Research output: Contribution to conference › Paper › peer-review

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abstract = "This paper formulates two-dimensional parametric cubic convolution for one-pass image restoration and reconstruction and derives a closed-form solution for the mean-square optimal parameters. The approach improves on traditional separable cubic convolution and relaxes the interpolation constraint to support restoration. The resulting kernel has five parameters and is designated 2D-5PCC-R. The closed-form solution for the optimal parameters is based on a continuous-discrete-continuous system model that accounts for the scene ensemble, acquisition blurring, sampling, noise, and processing. The analysis of the model leads to a simultaneous solution for five linear equations in the five parameters.",

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AU - Shi, Jiazheng

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AB - This paper formulates two-dimensional parametric cubic convolution for one-pass image restoration and reconstruction and derives a closed-form solution for the mean-square optimal parameters. The approach improves on traditional separable cubic convolution and relaxes the interpolation constraint to support restoration. The resulting kernel has five parameters and is designated 2D-5PCC-R. The closed-form solution for the optimal parameters is based on a continuous-discrete-continuous system model that accounts for the scene ensemble, acquisition blurring, sampling, noise, and processing. The analysis of the model leads to a simultaneous solution for five linear equations in the five parameters.

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ER -

Two-dimensional cubic convolution for one-pass image restoration and reconstruction

Abstract

Conference

ASJC Scopus subject areas

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