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Video texture analysis for VVC content
Examining video characteristics, particularly leveraging filters such as Canny and calculating image standard deviation, prior to the video coding process is a crucial preprocessing step that enhances the efficiency and quality of the coding workflow. By applying filters like Canny, valuable insight...
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creator | Fatma, Belghith Taheni, Damak Sonda, Ben Jdidia Bouthaina, Abdallah Ali, Ben Ayed Mohamed Nouri, Masmoudi |
description | Examining video characteristics, particularly leveraging filters such as Canny and calculating image standard deviation, prior to the video coding process is a crucial preprocessing step that enhances the efficiency and quality of the coding workflow. By applying filters like Canny, valuable insights into the spatial distribution of edges are gained, enabling precise identification of regions with varying complexity. Simultaneously, the calculation of standard deviation provides a quantitative measure of pixel intensity variations, aiding in the assessment of overall image texture. This meticulous analysis, as proposed by our method, enables the optimization of coding parameters, including the selection of suitable compression algorithms and the refinement of spatial and temporal redundancy reduction strategies. Ultimately, the strategic incorporation of filter-based analyses in the preprocessing phase not only refines video coding processes but also lays the foundation for improved compression outcomes, addressing the unique characteristics of each video sequence with precision. |
doi_str_mv | 10.1109/ATSIP62566.2024.10639036 |
format | conference_proceeding |
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Ultimately, the strategic incorporation of filter-based analyses in the preprocessing phase not only refines video coding processes but also lays the foundation for improved compression outcomes, addressing the unique characteristics of each video sequence with precision.</description><subject>Canny</subject><subject>Filters</subject><subject>Graphical models</subject><subject>Image coding</subject><subject>Image edge detection</subject><subject>Image texture</subject><subject>standard deviation</subject><subject>texture</subject><subject>Video coding</subject><subject>Video content</subject><subject>Video sequences</subject><issn>2687-878X</issn><isbn>9798350351484</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2024</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1j81Kw0AURkdBsLR5Axezcpd4Z25yZ2ZZgj-FgkJrcFdmkjswUhNJIti3t6CuvrM6h08IqaBQCtzder_bvJCuiAoNuiwUEDpAuhCZM85iBVip0paXYqHJmtwa-3Ytsml6BwDUgFbRQtw2qeNBzvw9f40sfe-PpylNMg6jbJpatkM_cz-vxFX0x4mzv12K14f7ff2Ub58fN_V6m6dzfs4DIivfRgPYKaTKmDYSG-8CVFETa6NbZTVEBld2yoQzlIFj6JwH0hGX4ubXm5j58DmmDz-eDv_X8AcBc0Ko</recordid><startdate>20240711</startdate><enddate>20240711</enddate><creator>Fatma, Belghith</creator><creator>Taheni, Damak</creator><creator>Sonda, Ben Jdidia</creator><creator>Bouthaina, Abdallah</creator><creator>Ali, Ben Ayed Mohamed</creator><creator>Nouri, Masmoudi</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20240711</creationdate><title>Video texture analysis for VVC content</title><author>Fatma, Belghith ; Taheni, Damak ; Sonda, Ben Jdidia ; Bouthaina, Abdallah ; Ali, Ben Ayed Mohamed ; Nouri, Masmoudi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i106t-b33e1acf703d136577cf6e7a9b05f26e272c1820fe094d17bfe04befbd9a062f3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Canny</topic><topic>Filters</topic><topic>Graphical models</topic><topic>Image coding</topic><topic>Image edge detection</topic><topic>Image texture</topic><topic>standard deviation</topic><topic>texture</topic><topic>Video coding</topic><topic>Video content</topic><topic>Video sequences</topic><toplevel>online_resources</toplevel><creatorcontrib>Fatma, Belghith</creatorcontrib><creatorcontrib>Taheni, Damak</creatorcontrib><creatorcontrib>Sonda, Ben Jdidia</creatorcontrib><creatorcontrib>Bouthaina, Abdallah</creatorcontrib><creatorcontrib>Ali, Ben Ayed Mohamed</creatorcontrib><creatorcontrib>Nouri, Masmoudi</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Fatma, Belghith</au><au>Taheni, Damak</au><au>Sonda, Ben Jdidia</au><au>Bouthaina, Abdallah</au><au>Ali, Ben Ayed Mohamed</au><au>Nouri, Masmoudi</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Video texture analysis for VVC content</atitle><btitle>2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP)</btitle><stitle>ATSIP</stitle><date>2024-07-11</date><risdate>2024</risdate><volume>1</volume><spage>223</spage><epage>227</epage><pages>223-227</pages><eissn>2687-878X</eissn><eisbn>9798350351484</eisbn><abstract>Examining video characteristics, particularly leveraging filters such as Canny and calculating image standard deviation, prior to the video coding process is a crucial preprocessing step that enhances the efficiency and quality of the coding workflow. By applying filters like Canny, valuable insights into the spatial distribution of edges are gained, enabling precise identification of regions with varying complexity. Simultaneously, the calculation of standard deviation provides a quantitative measure of pixel intensity variations, aiding in the assessment of overall image texture. This meticulous analysis, as proposed by our method, enables the optimization of coding parameters, including the selection of suitable compression algorithms and the refinement of spatial and temporal redundancy reduction strategies. Ultimately, the strategic incorporation of filter-based analyses in the preprocessing phase not only refines video coding processes but also lays the foundation for improved compression outcomes, addressing the unique characteristics of each video sequence with precision.</abstract><pub>IEEE</pub><doi>10.1109/ATSIP62566.2024.10639036</doi><tpages>5</tpages></addata></record> |
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identifier | EISSN: 2687-878X |
ispartof | 2024 IEEE 7th International Conference on Advanced Technologies, Signal and Image Processing (ATSIP), 2024, Vol.1, p.223-227 |
issn | 2687-878X |
language | eng |
recordid | cdi_ieee_primary_10639036 |
source | IEEE Xplore All Conference Series |
subjects | Canny Filters Graphical models Image coding Image edge detection Image texture standard deviation texture Video coding Video content Video sequences |
title | Video texture analysis for VVC content |
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