{"id":"https://openalex.org/W2608782665","doi":"https://doi.org/10.1109/icpr.2016.7899727","title":"Characterizing the structure tensor using gamma distributions","display_name":"Characterizing the structure tensor using gamma distributions","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2608782665","doi":"https://doi.org/10.1109/icpr.2016.7899727","mag":"2608782665"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7899727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899727","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://lup.lub.lu.se/record/3a7667c8-6add-41f6-a31f-f4601968c163","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5026331205","display_name":"Magnus Oskarsson","orcid":"https://orcid.org/0000-0002-1789-8094"},"institutions":[{"id":"https://openalex.org/I187531555","display_name":"Lund University","ror":"https://ror.org/012a77v79","country_code":"SE","type":"education","lineage":["https://openalex.org/I187531555"]}],"countries":["SE"],"is_corresponding":true,"raw_author_name":"Magnus Oskarsson","raw_affiliation_strings":["Centre for Mathematical Sciences, Lund University, Lund, Sweden"],"affiliations":[{"raw_affiliation_string":"Centre for Mathematical Sciences, Lund University, Lund, Sweden","institution_ids":["https://openalex.org/I187531555"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5026331205"],"corresponding_institution_ids":["https://openalex.org/I187531555"],"apc_list":null,"apc_paid":null,"fwci":0.167,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.61667813,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"763","last_page":"768"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/structure-tensor","display_name":"Structure tensor","score":0.8019888401031494},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.7244082093238831},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6720494627952576},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5541950464248657},{"id":"https://openalex.org/keywords/gaussian-noise","display_name":"Gaussian noise","score":0.5460346937179565},{"id":"https://openalex.org/keywords/gamma-distribution","display_name":"Gamma distribution","score":0.5120854377746582},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.48819905519485474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45569366216659546},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4505874514579773},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4497718811035156},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44938698410987854},{"id":"https://openalex.org/keywords/image-noise","display_name":"Image noise","score":0.44363126158714294},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3835851550102234},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34839048981666565},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11269930005073547},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.06855875253677368}],"concepts":[{"id":"https://openalex.org/C113315163","wikidata":"https://www.wikidata.org/wiki/Q7625159","display_name":"Structure tensor","level":3,"score":0.8019888401031494},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.7244082093238831},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6720494627952576},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5541950464248657},{"id":"https://openalex.org/C4199805","wikidata":"https://www.wikidata.org/wiki/Q2725903","display_name":"Gaussian noise","level":2,"score":0.5460346937179565},{"id":"https://openalex.org/C149717495","wikidata":"https://www.wikidata.org/wiki/Q117806","display_name":"Gamma distribution","level":2,"score":0.5120854377746582},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.48819905519485474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45569366216659546},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4505874514579773},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4497718811035156},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44938698410987854},{"id":"https://openalex.org/C35772409","wikidata":"https://www.wikidata.org/wiki/Q1323086","display_name":"Image noise","level":3,"score":0.44363126158714294},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3835851550102234},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34839048981666565},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11269930005073547},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.06855875253677368},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/icpr.2016.7899727","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899727","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:lup.lub.lu.se:3a7667c8-6add-41f6-a31f-f4601968c163","is_oa":true,"landing_page_url":"https://lup.lub.lu.se/record/3a7667c8-6add-41f6-a31f-f4601968c163","pdf_url":null,"source":{"id":"https://openalex.org/S4306400536","display_name":"Lund University Publications (Lund University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I187531555","host_organization_name":"Lund University","host_organization_lineage":["https://openalex.org/I187531555"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:lup.lub.lu.se:3a7667c8-6add-41f6-a31f-f4601968c163","is_oa":true,"landing_page_url":"https://lup.lub.lu.se/record/3a7667c8-6add-41f6-a31f-f4601968c163","pdf_url":null,"source":{"id":"https://openalex.org/S4306400536","display_name":"Lund University Publications (Lund University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I187531555","host_organization_name":"Lund University","host_organization_lineage":["https://openalex.org/I187531555"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"score":0.7699999809265137,"display_name":"No poverty","id":"https://metadata.un.org/sdg/1"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W1505723240","https://openalex.org/W1509918867","https://openalex.org/W1542873368","https://openalex.org/W1545934923","https://openalex.org/W1965555277","https://openalex.org/W1966105707","https://openalex.org/W1990208398","https://openalex.org/W2000594943","https://openalex.org/W2016309114","https://openalex.org/W2039060050","https://openalex.org/W2111308925","https://openalex.org/W2112515787","https://openalex.org/W2125015779","https://openalex.org/W2296333342","https://openalex.org/W2483969631","https://openalex.org/W6632552969","https://openalex.org/W6721930131","https://openalex.org/W6996289242"],"related_works":["https://openalex.org/W89301254","https://openalex.org/W2623954137","https://openalex.org/W2535084101","https://openalex.org/W2015754241","https://openalex.org/W1584319512","https://openalex.org/W1974463337","https://openalex.org/W2980586888","https://openalex.org/W1971932943","https://openalex.org/W2124371593","https://openalex.org/W2968266697"],"abstract_inverted_index":{"The":[0],"structure":[1,11,65],"tensor":[2,66],"is":[3],"a":[4,23],"powerful":[5,106],"tool":[6],"describing":[7],"the":[8,26,30,33,47,61,64,102,109],"local":[9],"intensity":[10],"of":[12,29,32,46,82],"an":[13,54],"image":[14,16,56],"or":[15],"sequence.":[17],"In":[18,35],"this":[19],"paper":[20],"we":[21,40],"give":[22],"model":[24,77,93],"for":[25,97,111],"noise":[27,62,92],"distribution":[28],"components":[31],"tensor.":[34],"order":[36],"to":[37,78],"do":[38],"so":[39],"have":[41],"also":[42],"investigated":[43],"some":[44],"properties":[45],"gamma":[48,72],"distribution.":[49],"We":[50,74,88],"show":[51,89],"that,":[52],"given":[53],"input":[55],"corrupted":[57],"with":[58],"Gaussian":[59],"noise,":[60],"in":[63,101],"can":[67,94],"be":[68,95],"modeled":[69],"well":[70],"by":[71],"distributions.":[73],"apply":[75],"our":[76,91],"automatic":[79,98],"contrast":[80],"enhancement":[81],"images":[83],"taken":[84],"under":[85],"poor":[86],"illumination.":[87],"how":[90],"used":[96],"parameter":[99,113],"selection":[100],"filtering":[103],"process,":[104],"giving":[105],"results":[107],"without":[108],"need":[110],"cumbersome":[112],"tuning.":[114]},"counts_by_year":[{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
