KANTENERHALTENDE VERBESSERUNG SEISMISCHER BILDER DURCH NICHTLINEARE ANISOTROPE DIFFUSION
rocessing a seismic image comprising the steps of(a) obtaining a two or three dimensional initial image data set, wherein each element u(m=0) of the data set is the initial image intensity of a point of the image;(b) calculating for each point the partial derivatives of u(m) in n directions to obtai...
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| creator | FEHMERS, CHRISTIAAN KALITZIN, NIKOLOV BOUTS, ERIK |
| description | rocessing a seismic image comprising the steps of(a) obtaining a two or three dimensional initial image data set, wherein each element u(m=0) of the data set is the initial image intensity of a point of the image;(b) calculating for each point the partial derivatives of u(m) in n directions to obtain n derivative data sets of the partial derivatives uxi; (c) calculating for each point a symmetric nxn structural matrix S, wherein the elements spq equal uxp.uxq, and an nxn diffusion matrix D, wherein the elements dij are a function of the elements spq; (d) calculating for each point u(m+1) from u(m) using the following equation u(m+1)=u(m)+c.div(epsil.Dgrad(u(m))), wherein c is a predetermined constant, 0 |
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(c) calculating for each point a symmetric nxn structural matrix S, wherein the elements spq equal uxp.uxq, and an nxn diffusion matrix D, wherein the elements dij are a function of the elements spq; (d) calculating for each point u(m+1) from u(m) using the following equation u(m+1)=u(m)+c.div(epsil.Dgrad(u(m))), wherein c is a predetermined constant, 0<=c<=1, and wherein epsil is a scalar, 0<=epsil<=, wherein epsil is close to zero when near an edge and close to 1 when far away from an edge (10, 11, 12, 14, 15); and(e) repeating steps (b) through (e) M times to obtain the processed image.</description><edition>7</edition><language>ger</language><subject>CALCULATING ; COMPUTING ; COUNTING ; DETECTING MASSES OR OBJECTS ; GEOPHYSICS ; GRAVITATIONAL MEASUREMENTS ; IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ; MEASURING ; PHYSICS ; TESTING</subject><creationdate>2005</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20050224&DB=EPODOC&CC=DE&NR=60102247T2$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,777,882,25545,76296</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20050224&DB=EPODOC&CC=DE&NR=60102247T2$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>FEHMERS, CHRISTIAAN</creatorcontrib><creatorcontrib>KALITZIN, NIKOLOV</creatorcontrib><creatorcontrib>BOUTS, ERIK</creatorcontrib><title>KANTENERHALTENDE VERBESSERUNG SEISMISCHER BILDER DURCH NICHTLINEARE ANISOTROPE DIFFUSION</title><description>rocessing a seismic image comprising the steps of(a) obtaining a two or three dimensional initial image data set, wherein each element u(m=0) of the data set is the initial image intensity of a point of the image;(b) calculating for each point the partial derivatives of u(m) in n directions to obtain n derivative data sets of the partial derivatives uxi; (c) calculating for each point a symmetric nxn structural matrix S, wherein the elements spq equal uxp.uxq, and an nxn diffusion matrix D, wherein the elements dij are a function of the elements spq; (d) calculating for each point u(m+1) from u(m) using the following equation u(m+1)=u(m)+c.div(epsil.Dgrad(u(m))), wherein c is a predetermined constant, 0<=c<=1, and wherein epsil is a scalar, 0<=epsil<=, wherein epsil is close to zero when near an edge and close to 1 when far away from an edge (10, 11, 12, 14, 15); and(e) repeating steps (b) through (e) M times to obtain the processed image.</description><subject>CALCULATING</subject><subject>COMPUTING</subject><subject>COUNTING</subject><subject>DETECTING MASSES OR OBJECTS</subject><subject>GEOPHYSICS</subject><subject>GRAVITATIONAL MEASUREMENTS</subject><subject>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</subject><subject>MEASURING</subject><subject>PHYSICS</subject><subject>TESTING</subject><fulltext>true</fulltext><rsrctype>patent</rsrctype><creationdate>2005</creationdate><recordtype>patent</recordtype><sourceid>EVB</sourceid><recordid>eNqNyrEKwjAQBuAuDqK-Q3AXahWd0-SvOaxXuUvFrRSJk2hB3x87-ABO3_JNs-vRcgRDgq1HPcwFUkIV0vLBKEhPpC5ATEm1H_GtuGCYXIg1MazAWCZtojRnGE9V1So1PM8m9_7xToufs2xZIbqwSsOrS--hv6Vn-nQeu3ydF8V2H2Ox-St9Aa-IMo8</recordid><startdate>20050224</startdate><enddate>20050224</enddate><creator>FEHMERS, CHRISTIAAN</creator><creator>KALITZIN, NIKOLOV</creator><creator>BOUTS, ERIK</creator><scope>EVB</scope></search><sort><creationdate>20050224</creationdate><title>KANTENERHALTENDE VERBESSERUNG SEISMISCHER BILDER DURCH NICHTLINEARE ANISOTROPE DIFFUSION</title><author>FEHMERS, CHRISTIAAN ; KALITZIN, NIKOLOV ; BOUTS, ERIK</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-epo_espacenet_DE60102247TT23</frbrgroupid><rsrctype>patents</rsrctype><prefilter>patents</prefilter><language>ger</language><creationdate>2005</creationdate><topic>CALCULATING</topic><topic>COMPUTING</topic><topic>COUNTING</topic><topic>DETECTING MASSES OR OBJECTS</topic><topic>GEOPHYSICS</topic><topic>GRAVITATIONAL MEASUREMENTS</topic><topic>IMAGE DATA PROCESSING OR GENERATION, IN GENERAL</topic><topic>MEASURING</topic><topic>PHYSICS</topic><topic>TESTING</topic><toplevel>online_resources</toplevel><creatorcontrib>FEHMERS, CHRISTIAAN</creatorcontrib><creatorcontrib>KALITZIN, NIKOLOV</creatorcontrib><creatorcontrib>BOUTS, ERIK</creatorcontrib><collection>esp@cenet</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>FEHMERS, CHRISTIAAN</au><au>KALITZIN, NIKOLOV</au><au>BOUTS, ERIK</au><format>patent</format><genre>patent</genre><ristype>GEN</ristype><title>KANTENERHALTENDE VERBESSERUNG SEISMISCHER BILDER DURCH NICHTLINEARE ANISOTROPE DIFFUSION</title><date>2005-02-24</date><risdate>2005</risdate><abstract>rocessing a seismic image comprising the steps of(a) obtaining a two or three dimensional initial image data set, wherein each element u(m=0) of the data set is the initial image intensity of a point of the image;(b) calculating for each point the partial derivatives of u(m) in n directions to obtain n derivative data sets of the partial derivatives uxi; (c) calculating for each point a symmetric nxn structural matrix S, wherein the elements spq equal uxp.uxq, and an nxn diffusion matrix D, wherein the elements dij are a function of the elements spq; (d) calculating for each point u(m+1) from u(m) using the following equation u(m+1)=u(m)+c.div(epsil.Dgrad(u(m))), wherein c is a predetermined constant, 0<=c<=1, and wherein epsil is a scalar, 0<=epsil<=, wherein epsil is close to zero when near an edge and close to 1 when far away from an edge (10, 11, 12, 14, 15); and(e) repeating steps (b) through (e) M times to obtain the processed image.</abstract><edition>7</edition><oa>free_for_read</oa></addata></record> |
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| subjects | CALCULATING COMPUTING COUNTING DETECTING MASSES OR OBJECTS GEOPHYSICS GRAVITATIONAL MEASUREMENTS IMAGE DATA PROCESSING OR GENERATION, IN GENERAL MEASURING PHYSICS TESTING |
| title | KANTENERHALTENDE VERBESSERUNG SEISMISCHER BILDER DURCH NICHTLINEARE ANISOTROPE DIFFUSION |
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