Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement

Elnaz Pashaei; Elham Pashaei; Nizamettin Aydin

doi:10.1007/978-3-030-51156-2_166

Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement

Elnaz Pashaei^*, Elham Pashaei, Nizamettin Aydin

^*Corresponding author for this work

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

7 Citations (Scopus)

Abstract

Image enhancement, aimed at improving the image contrast and information quality, is one of the most critical steps in image processing. Due to insufficient enhancement and the mean shift problem of conventional image enhancement techniques, new artificial intelligence-based image enhancement approaches have become an inevitable need in image processing. This paper employs the krill herd algorithm (KHA) and particle swarm optimization (PSO) to suggest a novel hybrid approach, called (PSOKHA) for image enhancement. The suggested PSOKHA method is used in search of optimum transfer function parameters to increase the quality of the images. For comparative evaluation, the performance of the PSOKHA is compared with six latest successful enhancement methods: PSO, KHA, screened Poisson equation (SPE), histogram equalization (HE), brightness preserving dynamic fuzzy HE (BPDFHE), and adaptive gamma correction weighted distribution (AGCWD). Experiments results in testing images include a medical image, a satellite image, and a handwritten image, demonstrate that the suggested strategy can produce better enhanced images in terms of several measurement criteria such as contrast, PSNR, entropy, and structure similarity index (SSIM).

Original language	English
Title of host publication	Intelligent and Fuzzy Techniques
Subtitle of host publication	Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference
Editors	Cengiz Kahraman, Sezi Cevik Onar, Basar Oztaysi, Irem Ucal Sari, Selcuk Cebi, A. Cagri Tolga
Publisher	Springer
Pages	1431-1439
Number of pages	9
ISBN (Print)	9783030511555
DOIs	https://doi.org/10.1007/978-3-030-51156-2_166
Publication status	Published - 2021
Externally published	Yes
Event	International Conference on Intelligent and Fuzzy Systems, INFUS 2020 - Istanbul, Turkey Duration: 21 Jul 2020 → 23 Jul 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1197 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	International Conference on Intelligent and Fuzzy Systems, INFUS 2020
Country/Territory	Turkey
City	Istanbul
Period	21/07/20 → 23/07/20

Bibliographical note

Publisher Copyright:
© 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

Image enhancement
Krill herd algorithm (KHA)
Particle swarm optimization (PSO)
SNPR

Access to Document

10.1007/978-3-030-51156-2_166

Cite this

Pashaei, E., Pashaei, E., & Aydin, N. (2021). Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement. In C. Kahraman, S. Cevik Onar, B. Oztaysi, I. U. Sari, S. Cebi, & A. C. Tolga (Eds.), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference (pp. 1431-1439). (Advances in Intelligent Systems and Computing; Vol. 1197 AISC). Springer. https://doi.org/10.1007/978-3-030-51156-2_166

Pashaei, Elnaz ; Pashaei, Elham ; Aydin, Nizamettin. / Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement. Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. editor / Cengiz Kahraman ; Sezi Cevik Onar ; Basar Oztaysi ; Irem Ucal Sari ; Selcuk Cebi ; A. Cagri Tolga. Springer, 2021. pp. 1431-1439 (Advances in Intelligent Systems and Computing).

@inproceedings{8422643ba7e64fc58dc0f6a0d5443de0,

title = "Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement",

abstract = "Image enhancement, aimed at improving the image contrast and information quality, is one of the most critical steps in image processing. Due to insufficient enhancement and the mean shift problem of conventional image enhancement techniques, new artificial intelligence-based image enhancement approaches have become an inevitable need in image processing. This paper employs the krill herd algorithm (KHA) and particle swarm optimization (PSO) to suggest a novel hybrid approach, called (PSOKHA) for image enhancement. The suggested PSOKHA method is used in search of optimum transfer function parameters to increase the quality of the images. For comparative evaluation, the performance of the PSOKHA is compared with six latest successful enhancement methods: PSO, KHA, screened Poisson equation (SPE), histogram equalization (HE), brightness preserving dynamic fuzzy HE (BPDFHE), and adaptive gamma correction weighted distribution (AGCWD). Experiments results in testing images include a medical image, a satellite image, and a handwritten image, demonstrate that the suggested strategy can produce better enhanced images in terms of several measurement criteria such as contrast, PSNR, entropy, and structure similarity index (SSIM).",

keywords = "Image enhancement, Krill herd algorithm (KHA), Particle swarm optimization (PSO), SNPR",

author = "Elnaz Pashaei and Elham Pashaei and Nizamettin Aydin",

note = "Publisher Copyright: {\textcopyright} 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG.; International Conference on Intelligent and Fuzzy Systems, INFUS 2020 ; Conference date: 21-07-2020 Through 23-07-2020",

year = "2021",

doi = "10.1007/978-3-030-51156-2_166",

language = "English",

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publisher = "Springer",

pages = "1431--1439",

editor = "Cengiz Kahraman and {Cevik Onar}, Sezi and Basar Oztaysi and Sari, {Irem Ucal} and Selcuk Cebi and Tolga, {A. Cagri}",

booktitle = "Intelligent and Fuzzy Techniques",

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Pashaei, E, Pashaei, E & Aydin, N 2021, Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement. in C Kahraman, S Cevik Onar, B Oztaysi, IU Sari, S Cebi & AC Tolga (eds), Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Advances in Intelligent Systems and Computing, vol. 1197 AISC, Springer, pp. 1431-1439, International Conference on Intelligent and Fuzzy Systems, INFUS 2020, Istanbul, Turkey, 21/07/20. https://doi.org/10.1007/978-3-030-51156-2_166

Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement. / Pashaei, Elnaz; Pashaei, Elham; Aydin, Nizamettin.
Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. ed. / Cengiz Kahraman; Sezi Cevik Onar; Basar Oztaysi; Irem Ucal Sari; Selcuk Cebi; A. Cagri Tolga. Springer, 2021. p. 1431-1439 (Advances in Intelligent Systems and Computing; Vol. 1197 AISC).

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

TY - GEN

T1 - Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement

AU - Pashaei, Elnaz

AU - Pashaei, Elham

AU - Aydin, Nizamettin

PY - 2021

Y1 - 2021

N2 - Image enhancement, aimed at improving the image contrast and information quality, is one of the most critical steps in image processing. Due to insufficient enhancement and the mean shift problem of conventional image enhancement techniques, new artificial intelligence-based image enhancement approaches have become an inevitable need in image processing. This paper employs the krill herd algorithm (KHA) and particle swarm optimization (PSO) to suggest a novel hybrid approach, called (PSOKHA) for image enhancement. The suggested PSOKHA method is used in search of optimum transfer function parameters to increase the quality of the images. For comparative evaluation, the performance of the PSOKHA is compared with six latest successful enhancement methods: PSO, KHA, screened Poisson equation (SPE), histogram equalization (HE), brightness preserving dynamic fuzzy HE (BPDFHE), and adaptive gamma correction weighted distribution (AGCWD). Experiments results in testing images include a medical image, a satellite image, and a handwritten image, demonstrate that the suggested strategy can produce better enhanced images in terms of several measurement criteria such as contrast, PSNR, entropy, and structure similarity index (SSIM).

AB - Image enhancement, aimed at improving the image contrast and information quality, is one of the most critical steps in image processing. Due to insufficient enhancement and the mean shift problem of conventional image enhancement techniques, new artificial intelligence-based image enhancement approaches have become an inevitable need in image processing. This paper employs the krill herd algorithm (KHA) and particle swarm optimization (PSO) to suggest a novel hybrid approach, called (PSOKHA) for image enhancement. The suggested PSOKHA method is used in search of optimum transfer function parameters to increase the quality of the images. For comparative evaluation, the performance of the PSOKHA is compared with six latest successful enhancement methods: PSO, KHA, screened Poisson equation (SPE), histogram equalization (HE), brightness preserving dynamic fuzzy HE (BPDFHE), and adaptive gamma correction weighted distribution (AGCWD). Experiments results in testing images include a medical image, a satellite image, and a handwritten image, demonstrate that the suggested strategy can produce better enhanced images in terms of several measurement criteria such as contrast, PSNR, entropy, and structure similarity index (SSIM).

KW - Image enhancement

KW - Krill herd algorithm (KHA)

KW - Particle swarm optimization (PSO)

KW - SNPR

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DO - 10.1007/978-3-030-51156-2_166

M3 - Conference contribution

AN - SCOPUS:85088745293

SN - 9783030511555

T3 - Advances in Intelligent Systems and Computing

SP - 1431

EP - 1439

BT - Intelligent and Fuzzy Techniques

A2 - Kahraman, Cengiz

A2 - Cevik Onar, Sezi

A2 - Oztaysi, Basar

A2 - Sari, Irem Ucal

A2 - Cebi, Selcuk

A2 - Tolga, A. Cagri

PB - Springer

T2 - International Conference on Intelligent and Fuzzy Systems, INFUS 2020

Y2 - 21 July 2020 through 23 July 2020

ER -

Pashaei E, Pashaei E, Aydin N. Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement. In Kahraman C, Cevik Onar S, Oztaysi B, Sari IU, Cebi S, Tolga AC, editors, Intelligent and Fuzzy Techniques: Smart and Innovative Solutions - Proceedings of the INFUS 2020 Conference. Springer. 2021. p. 1431-1439. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-51156-2_166

Hybrid Krill Herd Algorithm with Particle Swarm Optimization for Image Enhancement

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Keywords

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