Artificial bee Colony optimized image enhancement framework for invisible images
Image enhancement plays an important role in image processing to obtain an image with more perceptual details. In this paper, an artificial bee colony optimization based weighted gamma correction method is proposed to improve the visual quality of the contrast distorted images. The proposed method i...
Gespeichert in:
Veröffentlicht in: | Multimedia tools and applications 2023, Vol.82 (3), p.3627-3646 |
---|---|
Hauptverfasser: | , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 3646 |
---|---|
container_issue | 3 |
container_start_page | 3627 |
container_title | Multimedia tools and applications |
container_volume | 82 |
creator | Veluchamy, Magudeeswaran Subramani, Bharath |
description | Image enhancement plays an important role in image processing to obtain an image with more perceptual details. In this paper, an artificial bee colony optimization based weighted gamma correction method is proposed to improve the visual quality of the contrast distorted images. The proposed method improves the perceived contrast by expanding and compressing the pixel values. First, Image Expansion and Compression are employed to expose and confine the intensity level present in the image, respectively. Then, an optimally weighted sum approach is used to increase the essential details in the dark regions. Finally, an artificial bee colony optimization algorithm is employed to compute the optimal weighting parameter for brightness preservation. Experimental results demonstrate that the proposed method yields better visual quality images and highlights fine details by enhancing contrast and brightness. The proposed method’s quantitative results are competitive compared to the other well-known methods. |
doi_str_mv | 10.1007/s11042-022-13409-7 |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2760714572</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2760714572</sourcerecordid><originalsourceid>FETCH-LOGICAL-c319t-f6b203ffa89100e63626eeff4eba87f5d8c4f9934a77d8fddaeb4f5ce25e40b63</originalsourceid><addsrcrecordid>eNp9kLtOwzAUhi0EEqXwAkyWmA2-xslYVdykSjDAbDnJcXFJ4mKnoPL0GILExnTO8P3n8iF0zuglo1RfJcao5IRyTpiQtCL6AM2Y0oJozdlh7kVJiVaUHaOTlDaUskJxOUOPizh65xtvO1wD4GXowrDHYTv63n9Ci31v14BheLFDAz0MI3bR9vAR4it2IWI_vPvk6w4mMp2iI2e7BGe_dY6eb66flndk9XB7v1ysSCNYNRJX1JwK52xZ5QegEAUvAJyTUNtSO9WWjXRVJaTVui1d21qopVMNcAWS1oWYo4tp7jaGtx2k0WzCLg55peG6oJpJpXmm-EQ1MaQUwZltzHfGvWHUfJszkzmTzZkfc0bnkJhCKcPDGuLf6H9SXzTacmo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2760714572</pqid></control><display><type>article</type><title>Artificial bee Colony optimized image enhancement framework for invisible images</title><source>Springer Nature - Complete Springer Journals</source><creator>Veluchamy, Magudeeswaran ; Subramani, Bharath</creator><creatorcontrib>Veluchamy, Magudeeswaran ; Subramani, Bharath</creatorcontrib><description>Image enhancement plays an important role in image processing to obtain an image with more perceptual details. In this paper, an artificial bee colony optimization based weighted gamma correction method is proposed to improve the visual quality of the contrast distorted images. The proposed method improves the perceived contrast by expanding and compressing the pixel values. First, Image Expansion and Compression are employed to expose and confine the intensity level present in the image, respectively. Then, an optimally weighted sum approach is used to increase the essential details in the dark regions. Finally, an artificial bee colony optimization algorithm is employed to compute the optimal weighting parameter for brightness preservation. Experimental results demonstrate that the proposed method yields better visual quality images and highlights fine details by enhancing contrast and brightness. The proposed method’s quantitative results are competitive compared to the other well-known methods.</description><identifier>ISSN: 1380-7501</identifier><identifier>EISSN: 1573-7721</identifier><identifier>DOI: 10.1007/s11042-022-13409-7</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithms ; Brightness ; Computer Communication Networks ; Computer Science ; Data Structures and Information Theory ; Image compression ; Image contrast ; Image enhancement ; Image processing ; Image quality ; Methods ; Multimedia ; Multimedia Information Systems ; Optimization ; Optimization algorithms ; Process controls ; Special Purpose and Application-Based Systems ; Swarm intelligence</subject><ispartof>Multimedia tools and applications, 2023, Vol.82 (3), p.3627-3646</ispartof><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022</rights><rights>The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-f6b203ffa89100e63626eeff4eba87f5d8c4f9934a77d8fddaeb4f5ce25e40b63</citedby><cites>FETCH-LOGICAL-c319t-f6b203ffa89100e63626eeff4eba87f5d8c4f9934a77d8fddaeb4f5ce25e40b63</cites><orcidid>0000-0001-8989-9320</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11042-022-13409-7$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11042-022-13409-7$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Veluchamy, Magudeeswaran</creatorcontrib><creatorcontrib>Subramani, Bharath</creatorcontrib><title>Artificial bee Colony optimized image enhancement framework for invisible images</title><title>Multimedia tools and applications</title><addtitle>Multimed Tools Appl</addtitle><description>Image enhancement plays an important role in image processing to obtain an image with more perceptual details. In this paper, an artificial bee colony optimization based weighted gamma correction method is proposed to improve the visual quality of the contrast distorted images. The proposed method improves the perceived contrast by expanding and compressing the pixel values. First, Image Expansion and Compression are employed to expose and confine the intensity level present in the image, respectively. Then, an optimally weighted sum approach is used to increase the essential details in the dark regions. Finally, an artificial bee colony optimization algorithm is employed to compute the optimal weighting parameter for brightness preservation. Experimental results demonstrate that the proposed method yields better visual quality images and highlights fine details by enhancing contrast and brightness. The proposed method’s quantitative results are competitive compared to the other well-known methods.</description><subject>Algorithms</subject><subject>Brightness</subject><subject>Computer Communication Networks</subject><subject>Computer Science</subject><subject>Data Structures and Information Theory</subject><subject>Image compression</subject><subject>Image contrast</subject><subject>Image enhancement</subject><subject>Image processing</subject><subject>Image quality</subject><subject>Methods</subject><subject>Multimedia</subject><subject>Multimedia Information Systems</subject><subject>Optimization</subject><subject>Optimization algorithms</subject><subject>Process controls</subject><subject>Special Purpose and Application-Based Systems</subject><subject>Swarm intelligence</subject><issn>1380-7501</issn><issn>1573-7721</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kLtOwzAUhi0EEqXwAkyWmA2-xslYVdykSjDAbDnJcXFJ4mKnoPL0GILExnTO8P3n8iF0zuglo1RfJcao5IRyTpiQtCL6AM2Y0oJozdlh7kVJiVaUHaOTlDaUskJxOUOPizh65xtvO1wD4GXowrDHYTv63n9Ci31v14BheLFDAz0MI3bR9vAR4it2IWI_vPvk6w4mMp2iI2e7BGe_dY6eb66flndk9XB7v1ysSCNYNRJX1JwK52xZ5QegEAUvAJyTUNtSO9WWjXRVJaTVui1d21qopVMNcAWS1oWYo4tp7jaGtx2k0WzCLg55peG6oJpJpXmm-EQ1MaQUwZltzHfGvWHUfJszkzmTzZkfc0bnkJhCKcPDGuLf6H9SXzTacmo</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Veluchamy, Magudeeswaran</creator><creator>Subramani, Bharath</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AL</scope><scope>8AO</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><orcidid>https://orcid.org/0000-0001-8989-9320</orcidid></search><sort><creationdate>2023</creationdate><title>Artificial bee Colony optimized image enhancement framework for invisible images</title><author>Veluchamy, Magudeeswaran ; Subramani, Bharath</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c319t-f6b203ffa89100e63626eeff4eba87f5d8c4f9934a77d8fddaeb4f5ce25e40b63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Brightness</topic><topic>Computer Communication Networks</topic><topic>Computer Science</topic><topic>Data Structures and Information Theory</topic><topic>Image compression</topic><topic>Image contrast</topic><topic>Image enhancement</topic><topic>Image processing</topic><topic>Image quality</topic><topic>Methods</topic><topic>Multimedia</topic><topic>Multimedia Information Systems</topic><topic>Optimization</topic><topic>Optimization algorithms</topic><topic>Process controls</topic><topic>Special Purpose and Application-Based Systems</topic><topic>Swarm intelligence</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Veluchamy, Magudeeswaran</creatorcontrib><creatorcontrib>Subramani, Bharath</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Computing Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>Multimedia tools and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Veluchamy, Magudeeswaran</au><au>Subramani, Bharath</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Artificial bee Colony optimized image enhancement framework for invisible images</atitle><jtitle>Multimedia tools and applications</jtitle><stitle>Multimed Tools Appl</stitle><date>2023</date><risdate>2023</risdate><volume>82</volume><issue>3</issue><spage>3627</spage><epage>3646</epage><pages>3627-3646</pages><issn>1380-7501</issn><eissn>1573-7721</eissn><abstract>Image enhancement plays an important role in image processing to obtain an image with more perceptual details. In this paper, an artificial bee colony optimization based weighted gamma correction method is proposed to improve the visual quality of the contrast distorted images. The proposed method improves the perceived contrast by expanding and compressing the pixel values. First, Image Expansion and Compression are employed to expose and confine the intensity level present in the image, respectively. Then, an optimally weighted sum approach is used to increase the essential details in the dark regions. Finally, an artificial bee colony optimization algorithm is employed to compute the optimal weighting parameter for brightness preservation. Experimental results demonstrate that the proposed method yields better visual quality images and highlights fine details by enhancing contrast and brightness. The proposed method’s quantitative results are competitive compared to the other well-known methods.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11042-022-13409-7</doi><tpages>20</tpages><orcidid>https://orcid.org/0000-0001-8989-9320</orcidid></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1380-7501 |
ispartof | Multimedia tools and applications, 2023, Vol.82 (3), p.3627-3646 |
issn | 1380-7501 1573-7721 |
language | eng |
recordid | cdi_proquest_journals_2760714572 |
source | Springer Nature - Complete Springer Journals |
subjects | Algorithms Brightness Computer Communication Networks Computer Science Data Structures and Information Theory Image compression Image contrast Image enhancement Image processing Image quality Methods Multimedia Multimedia Information Systems Optimization Optimization algorithms Process controls Special Purpose and Application-Based Systems Swarm intelligence |
title | Artificial bee Colony optimized image enhancement framework for invisible images |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-30T15%3A42%3A47IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Artificial%20bee%20Colony%20optimized%20image%20enhancement%20framework%20for%20invisible%20images&rft.jtitle=Multimedia%20tools%20and%20applications&rft.au=Veluchamy,%20Magudeeswaran&rft.date=2023&rft.volume=82&rft.issue=3&rft.spage=3627&rft.epage=3646&rft.pages=3627-3646&rft.issn=1380-7501&rft.eissn=1573-7721&rft_id=info:doi/10.1007/s11042-022-13409-7&rft_dat=%3Cproquest_cross%3E2760714572%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2760714572&rft_id=info:pmid/&rfr_iscdi=true |