Single frame image super resolution using ANFIS interpolation: An initial experiment-based approach

Muhammad Ismail; Jing Yang; Changjing Shang; Qiang Shen

doi:10.1007/978-3-030-29933-0_3

Single frame image super resolution using ANFIS interpolation: An initial experiment-based approach

Muhammad Ismail, Jing Yang, Changjing Shang, Qiang Shen

Adran Cyfrifiadureg

Sukkur IBA University

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

2 Dyfyniadau (Scopus)

59 Wedi eu Llwytho i Lawr (Pure)

Crynodeb

Image super resolution is a classical problem in image processing. Different from most of the existing super resolution algorithms that work on sufficient training data, in this work, a new super resolution method is proposed to handle the situation where the training data is insufficient by the use of ANFIS (Adaptive Network-based Fuzzy Inference System) interpolation. ANFIS interpolation aims to interpolate an effective ANFIS given only sparse data in the problem area of interest, with the assistance of two well trained ANFISs in the neighbourhood areas. The interpolated ANFIS constructs mappings from low resolution images to high resolution ones, which provides an effective mechanism for further inference of high resolution images from given low resolution ones. Experimental results indicate that the proposed approach entails improved super resolution performance for situations where there is a shortage of training data.

Iaith wreiddiol	Saesneg
Teitl	Advances in Computational Intelligence Systems
Is-deitl	Contributions Presented at the 19th UK Workshop on Computational Intelligence, 2019
Golygyddion	Zhaojie Ju, Dalin Zhou, Alexander Gegov, Longzhi Yang, Chenguang Yang
Cyhoeddwr	Springer Nature
Tudalennau	27-40
Nifer y tudalennau	14
Cyfrol	1043
ISBN (Electronig)	978-3-030-29933-0
ISBN (Argraffiad)	978-3-030-29932-3
Dynodwyr Gwrthrych Digidol (DOIs)	https://doi.org/10.1007/978-3-030-29933-0_3
Statws	Cyhoeddwyd - 30 Awst 2019
Digwyddiad	UK Workshop on Computational Intelligence - University of Portsmouth, Portsmouth, Teyrnas Unedig Prydain Fawr a Gogledd Iwerddon Hyd: 04 Medi 2019 → 05 Medi 2019 Rhif y gynhadledd: 19 https://www.ukci2019.port.ac.uk/

Cyfres gyhoeddiadau

Enw	Advances in Intelligent Systems and Computing
Cyfrol	1043
ISSN (Argraffiad)	2194-5357
ISSN (Electronig)	2194-5365

Gweithdy

Gweithdy	UK Workshop on Computational Intelligence
Teitl cryno	UKCI 2019
Gwlad/Tiriogaeth	Teyrnas Unedig Prydain Fawr a Gogledd Iwerddon
Dinas	Portsmouth
Cyfnod	04 Medi 2019 → 05 Medi 2019
Cyfeiriad rhyngrwyd	https://www.ukci2019.port.ac.uk/

Mynediad at Ddogfen

10.1007/978-3-030-29933-0_3

Accepted ManuscriptLlawysgrif awdur wedi’i dderbyn, 5.15 MB

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Dolen i’r cyhoeddiad yn Scopus

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Ismail, M., Yang, J., Shang, C., & Shen, Q. (2019). Single frame image super resolution using ANFIS interpolation: An initial experiment-based approach. Yn Z. Ju, D. Zhou, A. Gegov, L. Yang, & C. Yang (Gol.), Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, 2019 (Cyfrol 1043, tt. 27-40). (Advances in Intelligent Systems and Computing; Cyfrol 1043). Springer Nature. https://doi.org/10.1007/978-3-030-29933-0_3

Ismail, Muhammad ; Yang, Jing ; Shang, Changjing et al. / Single frame image super resolution using ANFIS interpolation : An initial experiment-based approach. Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, 2019. Gol. / Zhaojie Ju ; Dalin Zhou ; Alexander Gegov ; Longzhi Yang ; Chenguang Yang. Cyfrol 1043 Springer Nature, 2019. tt. 27-40 (Advances in Intelligent Systems and Computing).

@inproceedings{56858ce95f214cebbc045fe7dbad4898,

title = "Single frame image super resolution using ANFIS interpolation: An initial experiment-based approach",

abstract = "Image super resolution is a classical problem in image processing. Different from most of the existing super resolution algorithms that work on sufficient training data, in this work, a new super resolution method is proposed to handle the situation where the training data is insufficient by the use of ANFIS (Adaptive Network-based Fuzzy Inference System) interpolation. ANFIS interpolation aims to interpolate an effective ANFIS given only sparse data in the problem area of interest, with the assistance of two well trained ANFISs in the neighbourhood areas. The interpolated ANFIS constructs mappings from low resolution images to high resolution ones, which provides an effective mechanism for further inference of high resolution images from given low resolution ones. Experimental results indicate that the proposed approach entails improved super resolution performance for situations where there is a shortage of training data.",

keywords = "Image Super Resolution, Insufficient training data, ANFIS interpolation, Image super resolution",

author = "Muhammad Ismail and Jing Yang and Changjing Shang and Qiang Shen",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; UK Workshop on Computational Intelligence, UKCI 2019 ; Conference date: 04-09-2019 Through 05-09-2019",

year = "2019",

month = aug,

day = "30",

doi = "10.1007/978-3-030-29933-0_3",

language = "English",

isbn = "978-3-030-29932-3",

volume = "1043",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer Nature",

pages = "27--40",

editor = "Zhaojie Ju and Dalin Zhou and Alexander Gegov and Longzhi Yang and Chenguang Yang",

booktitle = "Advances in Computational Intelligence Systems",

address = "Switzerland",

url = "https://www.ukci2019.port.ac.uk/",

}

Ismail, M, Yang, J, Shang, C & Shen, Q 2019, Single frame image super resolution using ANFIS interpolation: An initial experiment-based approach. yn Z Ju, D Zhou, A Gegov, L Yang & C Yang (gol.), Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, 2019. cyfrol. 1043, Advances in Intelligent Systems and Computing, cyfrol. 1043, Springer Nature, tt. 27-40, UK Workshop on Computational Intelligence, Portsmouth, Teyrnas Unedig Prydain Fawr a Gogledd Iwerddon, 04 Medi 2019. https://doi.org/10.1007/978-3-030-29933-0_3

Single frame image super resolution using ANFIS interpolation: An initial experiment-based approach. / Ismail, Muhammad; Yang, Jing; Shang, Changjing et al.
Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, 2019. gol. / Zhaojie Ju; Dalin Zhou; Alexander Gegov; Longzhi Yang; Chenguang Yang. Cyfrol 1043 Springer Nature, 2019. t. 27-40 (Advances in Intelligent Systems and Computing; Cyfrol 1043).

Allbwn ymchwil: Pennod mewn Llyfr/Adroddiad/Trafodion Cynhadledd › Trafodion Cynhadledd (Nid-Cyfnodolyn fathau)

TY - GEN

T1 - Single frame image super resolution using ANFIS interpolation

T2 - UK Workshop on Computational Intelligence

AU - Ismail, Muhammad

AU - Yang, Jing

AU - Shang, Changjing

AU - Shen, Qiang

N1 - Conference code: 19

PY - 2019/8/30

Y1 - 2019/8/30

N2 - Image super resolution is a classical problem in image processing. Different from most of the existing super resolution algorithms that work on sufficient training data, in this work, a new super resolution method is proposed to handle the situation where the training data is insufficient by the use of ANFIS (Adaptive Network-based Fuzzy Inference System) interpolation. ANFIS interpolation aims to interpolate an effective ANFIS given only sparse data in the problem area of interest, with the assistance of two well trained ANFISs in the neighbourhood areas. The interpolated ANFIS constructs mappings from low resolution images to high resolution ones, which provides an effective mechanism for further inference of high resolution images from given low resolution ones. Experimental results indicate that the proposed approach entails improved super resolution performance for situations where there is a shortage of training data.

AB - Image super resolution is a classical problem in image processing. Different from most of the existing super resolution algorithms that work on sufficient training data, in this work, a new super resolution method is proposed to handle the situation where the training data is insufficient by the use of ANFIS (Adaptive Network-based Fuzzy Inference System) interpolation. ANFIS interpolation aims to interpolate an effective ANFIS given only sparse data in the problem area of interest, with the assistance of two well trained ANFISs in the neighbourhood areas. The interpolated ANFIS constructs mappings from low resolution images to high resolution ones, which provides an effective mechanism for further inference of high resolution images from given low resolution ones. Experimental results indicate that the proposed approach entails improved super resolution performance for situations where there is a shortage of training data.

KW - Image Super Resolution

KW - Insufficient training data

KW - ANFIS interpolation

KW - Image super resolution

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U2 - 10.1007/978-3-030-29933-0_3

DO - 10.1007/978-3-030-29933-0_3

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SN - 978-3-030-29932-3

VL - 1043

T3 - Advances in Intelligent Systems and Computing

SP - 27

EP - 40

BT - Advances in Computational Intelligence Systems

A2 - Ju, Zhaojie

A2 - Zhou, Dalin

A2 - Gegov, Alexander

A2 - Yang, Longzhi

A2 - Yang, Chenguang

PB - Springer Nature

Y2 - 4 September 2019 through 5 September 2019

ER -

Ismail M, Yang J, Shang C , Shen Q. Single frame image super resolution using ANFIS interpolation: An initial experiment-based approach. Yn Ju Z, Zhou D, Gegov A, Yang L, Yang C, golygyddion, Advances in Computational Intelligence Systems: Contributions Presented at the 19th UK Workshop on Computational Intelligence, 2019. Cyfrol 1043. Springer Nature. 2019. t. 27-40. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-29933-0_3

Single frame image super resolution using ANFIS interpolation: An initial experiment-based approach

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