Image representation method based on Gaussian function and non-uniform partition

Image representation or reconstruction methods are important in digital image processing. Due to different image features happening in different regions, in this work, an image representation algorithm based on Gaussian function and non-uniform partition is proposed to represent the image with diffe...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Multimedia tools and applications 2023, Vol.82 (1), p.839-861
Hauptverfasser: Zhao, WeiKang, U, KinTak, Luo, HuiBin
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 861
container_issue 1
container_start_page 839
container_title Multimedia tools and applications
container_volume 82
creator Zhao, WeiKang
U, KinTak
Luo, HuiBin
description Image representation or reconstruction methods are important in digital image processing. Due to different image features happening in different regions, in this work, an image representation algorithm based on Gaussian function and non-uniform partition is proposed to represent the image with different functions in non-uniform regions. That means the pixel values in each region can be approximated by an extension of the Gaussian function after applying the least square approximation. The experimental results prove that the proposed algorithm has better performance than other non-uniform partition algorithms in terms of reconstructed image quality and time complexity. In addition, the partition mesh density can reflect the texture complexity of image regions and help to determine where the watermark can be embedded. Therefore, a novel watermark algorithm based on the proposed non-uniform partition is constructed and tested. The results show that it can embed a big gray watermark into the host image without causing its obvious distortion. This indicates some of the advantages of the proposed image representation algorithm.
doi_str_mv 10.1007/s11042-022-13213-3
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_2758755813</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2758755813</sourcerecordid><originalsourceid>FETCH-LOGICAL-c249t-c22342a65dbb8cacaa5cd73726a040015568127f845f95d89816d99b6b6a49d43</originalsourceid><addsrcrecordid>eNp9kD1PwzAQhi0EEqXwB5gsMRv8GTsjqqCtVAkGmK1L7JRUxAl2MvDvcRskNpb70L3v3elB6JbRe0apfkiMUckJ5ZwwwZkg4gwtmNKCaM3Zea6FoUQryi7RVUoHSlmhuFyg120He4-jH6JPPowwtn3AnR8_eocrSN7h3K9hSqmFgJsp1CcFBIdDH8gU2qaPHR4gju1xco0uGvhM_uY3L9H789PbakN2L-vt6nFHai7LMUcuJIdCuaoyNdQAqnZaaF4Alfk7pQrDuG6MVE2pnCkNK1xZVkVVgCydFEt0N-8dYv81-TTaQz_FkE9arpXRShkmsorPqjr2KUXf2CG2HcRvy6g9krMzOZvJ2RM5ezSJ2ZSyOOx9_Fv9j-sHGmxwqQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2758755813</pqid></control><display><type>article</type><title>Image representation method based on Gaussian function and non-uniform partition</title><source>Springer Online Journals</source><creator>Zhao, WeiKang ; U, KinTak ; Luo, HuiBin</creator><creatorcontrib>Zhao, WeiKang ; U, KinTak ; Luo, HuiBin</creatorcontrib><description>Image representation or reconstruction methods are important in digital image processing. Due to different image features happening in different regions, in this work, an image representation algorithm based on Gaussian function and non-uniform partition is proposed to represent the image with different functions in non-uniform regions. That means the pixel values in each region can be approximated by an extension of the Gaussian function after applying the least square approximation. The experimental results prove that the proposed algorithm has better performance than other non-uniform partition algorithms in terms of reconstructed image quality and time complexity. In addition, the partition mesh density can reflect the texture complexity of image regions and help to determine where the watermark can be embedded. Therefore, a novel watermark algorithm based on the proposed non-uniform partition is constructed and tested. The results show that it can embed a big gray watermark into the host image without causing its obvious distortion. This indicates some of the advantages of the proposed image representation algorithm.</description><identifier>ISSN: 1380-7501</identifier><identifier>EISSN: 1573-7721</identifier><identifier>DOI: 10.1007/s11042-022-13213-3</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Algorithms ; Approximation ; Complexity ; Computer Communication Networks ; Computer Science ; Data Structures and Information Theory ; Digital imaging ; Image processing ; Image quality ; Image reconstruction ; Multimedia Information Systems ; Representations ; Special Purpose and Application-Based Systems ; Watermarking</subject><ispartof>Multimedia tools and applications, 2023, Vol.82 (1), p.839-861</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-c249t-c22342a65dbb8cacaa5cd73726a040015568127f845f95d89816d99b6b6a49d43</citedby><cites>FETCH-LOGICAL-c249t-c22342a65dbb8cacaa5cd73726a040015568127f845f95d89816d99b6b6a49d43</cites><orcidid>0000-0001-6222-6927</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/s11042-022-13213-3$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11042-022-13213-3$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>315,781,785,27926,27927,41490,42559,51321</link.rule.ids></links><search><creatorcontrib>Zhao, WeiKang</creatorcontrib><creatorcontrib>U, KinTak</creatorcontrib><creatorcontrib>Luo, HuiBin</creatorcontrib><title>Image representation method based on Gaussian function and non-uniform partition</title><title>Multimedia tools and applications</title><addtitle>Multimed Tools Appl</addtitle><description>Image representation or reconstruction methods are important in digital image processing. Due to different image features happening in different regions, in this work, an image representation algorithm based on Gaussian function and non-uniform partition is proposed to represent the image with different functions in non-uniform regions. That means the pixel values in each region can be approximated by an extension of the Gaussian function after applying the least square approximation. The experimental results prove that the proposed algorithm has better performance than other non-uniform partition algorithms in terms of reconstructed image quality and time complexity. In addition, the partition mesh density can reflect the texture complexity of image regions and help to determine where the watermark can be embedded. Therefore, a novel watermark algorithm based on the proposed non-uniform partition is constructed and tested. The results show that it can embed a big gray watermark into the host image without causing its obvious distortion. This indicates some of the advantages of the proposed image representation algorithm.</description><subject>Algorithms</subject><subject>Approximation</subject><subject>Complexity</subject><subject>Computer Communication Networks</subject><subject>Computer Science</subject><subject>Data Structures and Information Theory</subject><subject>Digital imaging</subject><subject>Image processing</subject><subject>Image quality</subject><subject>Image reconstruction</subject><subject>Multimedia Information Systems</subject><subject>Representations</subject><subject>Special Purpose and Application-Based Systems</subject><subject>Watermarking</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>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kD1PwzAQhi0EEqXwB5gsMRv8GTsjqqCtVAkGmK1L7JRUxAl2MvDvcRskNpb70L3v3elB6JbRe0apfkiMUckJ5ZwwwZkg4gwtmNKCaM3Zea6FoUQryi7RVUoHSlmhuFyg120He4-jH6JPPowwtn3AnR8_eocrSN7h3K9hSqmFgJsp1CcFBIdDH8gU2qaPHR4gju1xco0uGvhM_uY3L9H789PbakN2L-vt6nFHai7LMUcuJIdCuaoyNdQAqnZaaF4Alfk7pQrDuG6MVE2pnCkNK1xZVkVVgCydFEt0N-8dYv81-TTaQz_FkE9arpXRShkmsorPqjr2KUXf2CG2HcRvy6g9krMzOZvJ2RM5ezSJ2ZSyOOx9_Fv9j-sHGmxwqQ</recordid><startdate>2023</startdate><enddate>2023</enddate><creator>Zhao, WeiKang</creator><creator>U, KinTak</creator><creator>Luo, HuiBin</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/0000-0001-6222-6927</orcidid></search><sort><creationdate>2023</creationdate><title>Image representation method based on Gaussian function and non-uniform partition</title><author>Zhao, WeiKang ; U, KinTak ; Luo, HuiBin</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c249t-c22342a65dbb8cacaa5cd73726a040015568127f845f95d89816d99b6b6a49d43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Algorithms</topic><topic>Approximation</topic><topic>Complexity</topic><topic>Computer Communication Networks</topic><topic>Computer Science</topic><topic>Data Structures and Information Theory</topic><topic>Digital imaging</topic><topic>Image processing</topic><topic>Image quality</topic><topic>Image reconstruction</topic><topic>Multimedia Information Systems</topic><topic>Representations</topic><topic>Special Purpose and Application-Based Systems</topic><topic>Watermarking</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Zhao, WeiKang</creatorcontrib><creatorcontrib>U, KinTak</creatorcontrib><creatorcontrib>Luo, HuiBin</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 Collection</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)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies &amp; Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</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>ProQuest research library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies &amp; Aerospace Database</collection><collection>ProQuest Advanced Technologies &amp; 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>Zhao, WeiKang</au><au>U, KinTak</au><au>Luo, HuiBin</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Image representation method based on Gaussian function and non-uniform partition</atitle><jtitle>Multimedia tools and applications</jtitle><stitle>Multimed Tools Appl</stitle><date>2023</date><risdate>2023</risdate><volume>82</volume><issue>1</issue><spage>839</spage><epage>861</epage><pages>839-861</pages><issn>1380-7501</issn><eissn>1573-7721</eissn><abstract>Image representation or reconstruction methods are important in digital image processing. Due to different image features happening in different regions, in this work, an image representation algorithm based on Gaussian function and non-uniform partition is proposed to represent the image with different functions in non-uniform regions. That means the pixel values in each region can be approximated by an extension of the Gaussian function after applying the least square approximation. The experimental results prove that the proposed algorithm has better performance than other non-uniform partition algorithms in terms of reconstructed image quality and time complexity. In addition, the partition mesh density can reflect the texture complexity of image regions and help to determine where the watermark can be embedded. Therefore, a novel watermark algorithm based on the proposed non-uniform partition is constructed and tested. The results show that it can embed a big gray watermark into the host image without causing its obvious distortion. This indicates some of the advantages of the proposed image representation algorithm.</abstract><cop>New York</cop><pub>Springer US</pub><doi>10.1007/s11042-022-13213-3</doi><tpages>23</tpages><orcidid>https://orcid.org/0000-0001-6222-6927</orcidid></addata></record>
fulltext fulltext
identifier ISSN: 1380-7501
ispartof Multimedia tools and applications, 2023, Vol.82 (1), p.839-861
issn 1380-7501
1573-7721
language eng
recordid cdi_proquest_journals_2758755813
source Springer Online Journals
subjects Algorithms
Approximation
Complexity
Computer Communication Networks
Computer Science
Data Structures and Information Theory
Digital imaging
Image processing
Image quality
Image reconstruction
Multimedia Information Systems
Representations
Special Purpose and Application-Based Systems
Watermarking
title Image representation method based on Gaussian function and non-uniform partition
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-17T17%3A36%3A19IST&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=Image%20representation%20method%20based%20on%20Gaussian%20function%20and%20non-uniform%20partition&rft.jtitle=Multimedia%20tools%20and%20applications&rft.au=Zhao,%20WeiKang&rft.date=2023&rft.volume=82&rft.issue=1&rft.spage=839&rft.epage=861&rft.pages=839-861&rft.issn=1380-7501&rft.eissn=1573-7721&rft_id=info:doi/10.1007/s11042-022-13213-3&rft_dat=%3Cproquest_cross%3E2758755813%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=2758755813&rft_id=info:pmid/&rfr_iscdi=true