Regularized multichannel restoration approach for globally optimal high-resolution video sequence

Min Cheol Hong; Moon Gi Kang; Aggelos K. Katsaggelos

doi:10.1117/12.263211

Regularized multichannel restoration approach for globally optimal high-resolution video sequence

Min Cheol Hong, Moon Gi Kang, Aggelos K. Katsaggelos

Department of Electrical and Electronic Engineering

Research output: Contribution to journal › Conference article › peer-review

20 Citations (Scopus)

Abstract

This paper introduces an iterative regularized approach to obtain a high resolution video sequence. A multiple input smoothing convex functional is defined and used to obtain a globally optimal high resolution video sequence. A mathematical model of multiple inputs is described by using the point spread function between the original and bilinearly interpolated images in the spatial domain, and motion estimation between frames in the temporal domain. Properties of the proposed smoothing convex functional are analyzed. An iterative algorithm is utilized for obtaining a solution. The regularization parameter is updated at each iteration step from the partially restored video sequence. Experimental results demonstrate the capability of the proposed approach.

Original language	English
Pages (from-to)	1306-1316
Number of pages	11
Journal	Proceedings of SPIE - The International Society for Optical Engineering
Volume	3024
DOIs	https://doi.org/10.1117/12.263211
Publication status	Published - 1997
Event	Visual Communications and Image Processing '97 - San Jose, CA, United States Duration: 1997 Feb 12 → 1997 Feb 12

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

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10.1117/12.263211

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title = "Regularized multichannel restoration approach for globally optimal high-resolution video sequence",

abstract = "This paper introduces an iterative regularized approach to obtain a high resolution video sequence. A multiple input smoothing convex functional is defined and used to obtain a globally optimal high resolution video sequence. A mathematical model of multiple inputs is described by using the point spread function between the original and bilinearly interpolated images in the spatial domain, and motion estimation between frames in the temporal domain. Properties of the proposed smoothing convex functional are analyzed. An iterative algorithm is utilized for obtaining a solution. The regularization parameter is updated at each iteration step from the partially restored video sequence. Experimental results demonstrate the capability of the proposed approach.",

author = "Hong, {Min Cheol} and Kang, {Moon Gi} and Katsaggelos, {Aggelos K.}",

year = "1997",

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journal = "Proceedings of SPIE - The International Society for Optical Engineering",

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note = "Visual Communications and Image Processing '97 ; Conference date: 12-02-1997 Through 12-02-1997",

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AU - Hong, Min Cheol

AU - Kang, Moon Gi

AU - Katsaggelos, Aggelos K.

PY - 1997

Y1 - 1997

N2 - This paper introduces an iterative regularized approach to obtain a high resolution video sequence. A multiple input smoothing convex functional is defined and used to obtain a globally optimal high resolution video sequence. A mathematical model of multiple inputs is described by using the point spread function between the original and bilinearly interpolated images in the spatial domain, and motion estimation between frames in the temporal domain. Properties of the proposed smoothing convex functional are analyzed. An iterative algorithm is utilized for obtaining a solution. The regularization parameter is updated at each iteration step from the partially restored video sequence. Experimental results demonstrate the capability of the proposed approach.

AB - This paper introduces an iterative regularized approach to obtain a high resolution video sequence. A multiple input smoothing convex functional is defined and used to obtain a globally optimal high resolution video sequence. A mathematical model of multiple inputs is described by using the point spread function between the original and bilinearly interpolated images in the spatial domain, and motion estimation between frames in the temporal domain. Properties of the proposed smoothing convex functional are analyzed. An iterative algorithm is utilized for obtaining a solution. The regularization parameter is updated at each iteration step from the partially restored video sequence. Experimental results demonstrate the capability of the proposed approach.

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VL - 3024

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EP - 1316

JO - Proceedings of SPIE - The International Society for Optical Engineering

JF - Proceedings of SPIE - The International Society for Optical Engineering

T2 - Visual Communications and Image Processing '97

Y2 - 12 February 1997 through 12 February 1997

ER -

Regularized multichannel restoration approach for globally optimal high-resolution video sequence

Abstract

All Science Journal Classification (ASJC) codes

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