An Edge-Preserving Multigrid-Like Technique for Image Denoising
Techniques based on the Well-Balanced Flow Equation have been employed as efficient tools for edge preserving noise removal. Although effective, this technique demands high computational effort, rendering it not practical in several applications. This work aims at proposing a multigrid like techniqu...
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creator | Ferraz, Carolina Toledo Nonato, Luis Gustavo Cuminato, José Alberto |
description | Techniques based on the Well-Balanced Flow Equation have been employed as efficient tools for edge preserving noise removal. Although effective, this technique demands high computational effort, rendering it not practical in several applications. This work aims at proposing a multigrid like technique for speeding up the solution of the Well-Balanced Flow equation. In fact, the diffusion equation is solved in a coarse grid and a coarse-to-fine error correction is applied in order to generate the desired solution. The transfer between coarser and finer grids is made by the Mitchell-Filter, a well known interpolation scheme that is designed for preserving edges. Numerical results are compared quantitative and qualitatively with other approaches, showing that our method produces similar image quality with much smaller computational time. |
doi_str_mv | 10.1007/11867586_12 |
format | Conference Proceeding |
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Although effective, this technique demands high computational effort, rendering it not practical in several applications. This work aims at proposing a multigrid like technique for speeding up the solution of the Well-Balanced Flow equation. In fact, the diffusion equation is solved in a coarse grid and a coarse-to-fine error correction is applied in order to generate the desired solution. The transfer between coarser and finer grids is made by the Mitchell-Filter, a well known interpolation scheme that is designed for preserving edges. Numerical results are compared quantitative and qualitatively with other approaches, showing that our method produces similar image quality with much smaller computational time.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 3540448918</identifier><identifier>ISBN: 9783540448914</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 3540448934</identifier><identifier>EISBN: 9783540448938</identifier><identifier>DOI: 10.1007/11867586_12</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Applied sciences ; Artificial intelligence ; Coarse Grid ; Computer science; control theory; systems ; Edge Detection ; Exact sciences and technology ; Image Denoising ; Multigrid Method ; Noisy Image ; Pattern recognition. Digital image processing. 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Although effective, this technique demands high computational effort, rendering it not practical in several applications. This work aims at proposing a multigrid like technique for speeding up the solution of the Well-Balanced Flow equation. In fact, the diffusion equation is solved in a coarse grid and a coarse-to-fine error correction is applied in order to generate the desired solution. The transfer between coarser and finer grids is made by the Mitchell-Filter, a well known interpolation scheme that is designed for preserving edges. Numerical results are compared quantitative and qualitatively with other approaches, showing that our method produces similar image quality with much smaller computational time.</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Coarse Grid</subject><subject>Computer science; control theory; systems</subject><subject>Edge Detection</subject><subject>Exact sciences and technology</subject><subject>Image Denoising</subject><subject>Multigrid Method</subject><subject>Noisy Image</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>3540448918</isbn><isbn>9783540448914</isbn><isbn>3540448934</isbn><isbn>9783540448938</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2006</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNpNkD1PwzAYhM2XRFuY-ANZGBgM7xs7cTwhVApUKoKhzJZjO8G0TYrdIvHvcVUkmG64R6e7I-QC4RoBxA1iVYqiKhXmB2TICg6cV5LxQzLAEpEyxuXRn4HVMRkAg5xKwdkpGcb4AQC5kPmA3N512cS2jr4GF1348l2bPW-XG98Gb-nML1w2d-a9859blzV9yKYr3brs3nW9jwk-IyeNXkZ3_qsj8vYwmY-f6OzlcTq-m9F1jnJDjeWSNwglhzo1YQKlNK6qGEpwgovCWNDIWc2NRKZTb23BNdYm0vG6YCNyuc9d62j0sgm6Mz6qdfArHb5Viks7yx13tedisrrWBVX3_SIqBLX7Tv37jv0AoANabg</recordid><startdate>2006</startdate><enddate>2006</enddate><creator>Ferraz, Carolina Toledo</creator><creator>Nonato, Luis Gustavo</creator><creator>Cuminato, José Alberto</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2006</creationdate><title>An Edge-Preserving Multigrid-Like Technique for Image Denoising</title><author>Ferraz, Carolina Toledo ; Nonato, Luis Gustavo ; Cuminato, José Alberto</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-p219t-cd494f10640b30237199ce883190e7475cd0a143b4c913a044ad0efdd371e4b53</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2006</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Coarse Grid</topic><topic>Computer science; control theory; systems</topic><topic>Edge Detection</topic><topic>Exact sciences and technology</topic><topic>Image Denoising</topic><topic>Multigrid Method</topic><topic>Noisy Image</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ferraz, Carolina Toledo</creatorcontrib><creatorcontrib>Nonato, Luis Gustavo</creatorcontrib><creatorcontrib>Cuminato, José Alberto</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ferraz, Carolina Toledo</au><au>Nonato, Luis Gustavo</au><au>Cuminato, José Alberto</au><au>Campilho, Aurélio</au><au>Kamel, Mohamed S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>An Edge-Preserving Multigrid-Like Technique for Image Denoising</atitle><btitle>Image Analysis and Recognition</btitle><date>2006</date><risdate>2006</risdate><spage>126</spage><epage>137</epage><pages>126-137</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>3540448918</isbn><isbn>9783540448914</isbn><eisbn>3540448934</eisbn><eisbn>9783540448938</eisbn><abstract>Techniques based on the Well-Balanced Flow Equation have been employed as efficient tools for edge preserving noise removal. Although effective, this technique demands high computational effort, rendering it not practical in several applications. This work aims at proposing a multigrid like technique for speeding up the solution of the Well-Balanced Flow equation. In fact, the diffusion equation is solved in a coarse grid and a coarse-to-fine error correction is applied in order to generate the desired solution. The transfer between coarser and finer grids is made by the Mitchell-Filter, a well known interpolation scheme that is designed for preserving edges. Numerical results are compared quantitative and qualitatively with other approaches, showing that our method produces similar image quality with much smaller computational time.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/11867586_12</doi><tpages>12</tpages></addata></record> |
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source | Springer Books |
subjects | Applied sciences Artificial intelligence Coarse Grid Computer science control theory systems Edge Detection Exact sciences and technology Image Denoising Multigrid Method Noisy Image Pattern recognition. Digital image processing. Computational geometry |
title | An Edge-Preserving Multigrid-Like Technique for Image Denoising |
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