The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks

Wai Chong Chia; Lee Seng Yeong; Sue Inn Ch'Ng; Yoke Lun Kam

doi:10.1109/SOCPAR.2015.7492770

The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks

Wai Chong Chia
, Lee Seng Yeong
, Sue Inn Ch'Ng
, Yoke Lun Kam

Sunway University

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

2 Citations (Scopus)

Abstract

In this paper, the effect of using multi-image and single-image super-resolution to reduce registration errors of low resolution images is evaluated. Two sets of low resolution images were captured using CMUCam4 to perform the evaluation. Moreover, a simplified method that make use of feature points extracted from resolution enhanced / upscaled images to improve the registration of low resolution images is also presented. The simulation results show that enhancing / upscaling the images in prior to registration does help to reduce the registration errors.

Original language	English
Title of host publication	Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015
Editors	Mario Koppen, Azah Kamilah Muda, Kun Ma, Bing Xue, Hideyuki Takagi, Ajith Abraham
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	340-345
Number of pages	6
ISBN (Electronic)	9781467393607
DOIs	https://doi.org/10.1109/SOCPAR.2015.7492770
Publication status	Published - 15 Jun 2016
Externally published	Yes
Event	7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 - Fukuoka, Japan Duration: 13 Nov 2015 → 15 Nov 2015

Publication series

Name	Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015

Conference

Conference	7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015
Country/Territory	Japan
City	Fukuoka
Period	13/11/15 → 15/11/15

Keywords

feature extraction
registration
sensor network
super-resolution

Access to Document

10.1109/SOCPAR.2015.7492770

Cite this

Chia, W. C., Yeong, L. S., Ch'Ng, S. I., & Kam, Y. L. (2016). The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks. In M. Koppen, A. K. Muda, K. Ma, B. Xue, H. Takagi, & A. Abraham (Eds.), Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 (pp. 340-345). Article 7492770 (Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SOCPAR.2015.7492770

Chia, Wai Chong ; Yeong, Lee Seng ; Ch'Ng, Sue Inn et al. / The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks. Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015. editor / Mario Koppen ; Azah Kamilah Muda ; Kun Ma ; Bing Xue ; Hideyuki Takagi ; Ajith Abraham. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 340-345 (Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015).

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title = "The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks",

abstract = "In this paper, the effect of using multi-image and single-image super-resolution to reduce registration errors of low resolution images is evaluated. Two sets of low resolution images were captured using CMUCam4 to perform the evaluation. Moreover, a simplified method that make use of feature points extracted from resolution enhanced / upscaled images to improve the registration of low resolution images is also presented. The simulation results show that enhancing / upscaling the images in prior to registration does help to reduce the registration errors.",

keywords = "feature extraction, registration, sensor network, super-resolution",

author = "Chia, \{Wai Chong\} and Yeong, \{Lee Seng\} and Ch'Ng, \{Sue Inn\} and Kam, \{Yoke Lun\}",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015 ; Conference date: 13-11-2015 Through 15-11-2015",

year = "2016",

month = jun,

day = "15",

doi = "10.1109/SOCPAR.2015.7492770",

language = "English",

series = "Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015",

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pages = "340--345",

editor = "Mario Koppen and Muda, \{Azah Kamilah\} and Kun Ma and Bing Xue and Hideyuki Takagi and Ajith Abraham",

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Chia, WC, Yeong, LS, Ch'Ng, SI & Kam, YL 2016, The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks. in M Koppen, AK Muda, K Ma, B Xue, H Takagi & A Abraham (eds), Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015., 7492770, Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015, Institute of Electrical and Electronics Engineers Inc., pp. 340-345, 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015, Fukuoka, Japan, 13/11/15. https://doi.org/10.1109/SOCPAR.2015.7492770

The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks. / Chia, Wai Chong; Yeong, Lee Seng; Ch'Ng, Sue Inn et al.
Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015. ed. / Mario Koppen; Azah Kamilah Muda; Kun Ma; Bing Xue; Hideyuki Takagi; Ajith Abraham. Institute of Electrical and Electronics Engineers Inc., 2016. p. 340-345 7492770 (Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015).

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

TY - GEN

T1 - The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks

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AU - Ch'Ng, Sue Inn

AU - Kam, Yoke Lun

PY - 2016/6/15

Y1 - 2016/6/15

N2 - In this paper, the effect of using multi-image and single-image super-resolution to reduce registration errors of low resolution images is evaluated. Two sets of low resolution images were captured using CMUCam4 to perform the evaluation. Moreover, a simplified method that make use of feature points extracted from resolution enhanced / upscaled images to improve the registration of low resolution images is also presented. The simulation results show that enhancing / upscaling the images in prior to registration does help to reduce the registration errors.

AB - In this paper, the effect of using multi-image and single-image super-resolution to reduce registration errors of low resolution images is evaluated. Two sets of low resolution images were captured using CMUCam4 to perform the evaluation. Moreover, a simplified method that make use of feature points extracted from resolution enhanced / upscaled images to improve the registration of low resolution images is also presented. The simulation results show that enhancing / upscaling the images in prior to registration does help to reduce the registration errors.

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KW - registration

KW - sensor network

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A2 - Koppen, Mario

A2 - Muda, Azah Kamilah

A2 - Ma, Kun

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A2 - Takagi, Hideyuki

A2 - Abraham, Ajith

PB - Institute of Electrical and Electronics Engineers Inc.

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Chia WC, Yeong LS, Ch'Ng SI, Kam YL. The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks. In Koppen M, Muda AK, Ma K, Xue B, Takagi H, Abraham A, editors, Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015. Institute of Electrical and Electronics Engineers Inc. 2016. p. 340-345. 7492770. (Proceedings of the 2015 7th International Conference of Soft Computing and Pattern Recognition, SoCPaR 2015). doi: 10.1109/SOCPAR.2015.7492770

The effect of using super-resolution to improve feature extraction and registration of low resolution images in sensor networks

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Keywords

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