Improved cubic convolution for two dimensional image reconstruction

Stephen E. Reichenbach; Frank Geng

Improved cubic convolution for two dimensional image reconstruction

Stephen E. Reichenbach, Frank Geng

Computer Science and Engineering

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

8 Scopus citations

Abstract

This paper describes improved piecewise cubic convolution for two-dimensional image reconstruction. Piecewise cubic convolution is one of the most popular methods for image reconstruction, but the traditional approach uses a separable two-dimensional convolution kernel that is based on a one-dimensional derivation. The traditional approach is sub-optimal for the usual case of non-separable scenes and systems. The improved approach implements the most general two-dimensional, non-separable, piecewise cubic interpolator with constraints for symmetry, continuity, and smoothness.

Original language	English (US)
Pages	1775-1778
Number of pages	4
State	Published - 2001
Event	2001 IEEE Nuclear Science Symposium Conference Record - San Diego, CA, United States Duration: Nov 4 2001 → Nov 10 2001

Conference

Conference	2001 IEEE Nuclear Science Symposium Conference Record
Country/Territory	United States
City	San Diego, CA
Period	11/4/01 → 11/10/01

ASJC Scopus subject areas

Radiation
Nuclear and High Energy Physics
Radiology Nuclear Medicine and imaging

Cite this

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title = "Improved cubic convolution for two dimensional image reconstruction",

abstract = "This paper describes improved piecewise cubic convolution for two-dimensional image reconstruction. Piecewise cubic convolution is one of the most popular methods for image reconstruction, but the traditional approach uses a separable two-dimensional convolution kernel that is based on a one-dimensional derivation. The traditional approach is sub-optimal for the usual case of non-separable scenes and systems. The improved approach implements the most general two-dimensional, non-separable, piecewise cubic interpolator with constraints for symmetry, continuity, and smoothness.",

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AU - Geng, Frank

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N2 - This paper describes improved piecewise cubic convolution for two-dimensional image reconstruction. Piecewise cubic convolution is one of the most popular methods for image reconstruction, but the traditional approach uses a separable two-dimensional convolution kernel that is based on a one-dimensional derivation. The traditional approach is sub-optimal for the usual case of non-separable scenes and systems. The improved approach implements the most general two-dimensional, non-separable, piecewise cubic interpolator with constraints for symmetry, continuity, and smoothness.

AB - This paper describes improved piecewise cubic convolution for two-dimensional image reconstruction. Piecewise cubic convolution is one of the most popular methods for image reconstruction, but the traditional approach uses a separable two-dimensional convolution kernel that is based on a one-dimensional derivation. The traditional approach is sub-optimal for the usual case of non-separable scenes and systems. The improved approach implements the most general two-dimensional, non-separable, piecewise cubic interpolator with constraints for symmetry, continuity, and smoothness.

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M3 - Paper

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T2 - 2001 IEEE Nuclear Science Symposium Conference Record

Y2 - 4 November 2001 through 10 November 2001

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Improved cubic convolution for two dimensional image reconstruction

Abstract

Conference

ASJC Scopus subject areas

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