Neural concurrent subsampling and interpolation for images

Jong Ok Kim; Byung Tae Choi; A. Morales; Sung Jea Ko

doi:10.1109/TENCON.1999.818674

Neural concurrent subsampling and interpolation for images

Jong Ok Kim, Byung Tae Choi, A. Morales, Sung Jea Ko

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Citations (Scopus)

Abstract

This paper presents a new method for image subsampling and interpolation based on the feedforward neural network (FNN). The proposed technique employs a single FNN with three hidden layers for both subsampling and interpolation, providing the advantages of high speed, parallel processing capability, and good image reproduction quality. Experimental results show that the proposed technique exhibits an increased performance over conventional ones.

Original language	English
Title of host publication	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1327-1330
Number of pages	4
ISBN (Electronic)	0780357396, 9780780357396
DOIs	https://doi.org/10.1109/TENCON.1999.818674
Publication status	Published - 1999
Event	1999 IEEE Region 10 Conference, TENCON 1999 - Cheju Island, Korea, Republic of Duration: 1999 Sept 15 → 1999 Sept 17

Publication series

Name	IEEE Region 10 Annual International Conference, Proceedings/TENCON
Volume	2
ISSN (Print)	2159-3442
ISSN (Electronic)	2159-3450

Other

Other	1999 IEEE Region 10 Conference, TENCON 1999
Country/Territory	Korea, Republic of
City	Cheju Island
Period	99/9/15 → 99/9/17

ASJC Scopus subject areas

Computer Science Applications
Electrical and Electronic Engineering

Access to Document

10.1109/TENCON.1999.818674

Cite this

Kim, J. O., Choi, B. T., Morales, A., & Ko, S. J. (1999). Neural concurrent subsampling and interpolation for images. In IEEE Region 10 Annual International Conference, Proceedings/TENCON (pp. 1327-1330). (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/TENCON.1999.818674

Neural concurrent subsampling and interpolation for images. / Kim, Jong Ok; Choi, Byung Tae; Morales, A. et al.
IEEE Region 10 Annual International Conference, Proceedings/TENCON. Institute of Electrical and Electronics Engineers Inc., 1999. p. 1327-1330 (IEEE Region 10 Annual International Conference, Proceedings/TENCON; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kim, JO, Choi, BT, Morales, A & Ko, SJ 1999, Neural concurrent subsampling and interpolation for images. in IEEE Region 10 Annual International Conference, Proceedings/TENCON. IEEE Region 10 Annual International Conference, Proceedings/TENCON, vol. 2, Institute of Electrical and Electronics Engineers Inc., pp. 1327-1330, 1999 IEEE Region 10 Conference, TENCON 1999, Cheju Island, Korea, Republic of, 99/9/15. https://doi.org/10.1109/TENCON.1999.818674

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abstract = "This paper presents a new method for image subsampling and interpolation based on the feedforward neural network (FNN). The proposed technique employs a single FNN with three hidden layers for both subsampling and interpolation, providing the advantages of high speed, parallel processing capability, and good image reproduction quality. Experimental results show that the proposed technique exhibits an increased performance over conventional ones.",

author = "Kim, {Jong Ok} and Choi, {Byung Tae} and A. Morales and Ko, {Sung Jea}",

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AB - This paper presents a new method for image subsampling and interpolation based on the feedforward neural network (FNN). The proposed technique employs a single FNN with three hidden layers for both subsampling and interpolation, providing the advantages of high speed, parallel processing capability, and good image reproduction quality. Experimental results show that the proposed technique exhibits an increased performance over conventional ones.

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ER -

Neural concurrent subsampling and interpolation for images

Abstract

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ASJC Scopus subject areas

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