{"id":"https://openalex.org/W2548390709","doi":"https://doi.org/10.1109/igarss.2016.7730652","title":"A self-adapted threshold-based region merging method for remote sensing image segmentation","display_name":"A self-adapted threshold-based region merging method for remote sensing image segmentation","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2548390709","doi":"https://doi.org/10.1109/igarss.2016.7730652","mag":"2548390709"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2016.7730652","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7730652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020105527","display_name":"Jian Yang","orcid":"https://orcid.org/0000-0001-6655-0898"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Jian Yang","raw_affiliation_strings":["Department of Geography & Planning, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Geography & Planning, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083745435","display_name":"Yuhong He","orcid":"https://orcid.org/0000-0003-4700-6517"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yuhong He","raw_affiliation_strings":["Department of Geography & Planning, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Geography & Planning, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045205524","display_name":"John P. Caspersen","orcid":"https://orcid.org/0000-0003-2931-9755"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"John Caspersen","raw_affiliation_strings":["Faculty of Forestry, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Faculty of Forestry, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5020105527"],"corresponding_institution_ids":["https://openalex.org/I185261750"],"apc_list":null,"apc_paid":null,"fwci":0.9689,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.81609921,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"6320","last_page":"6323"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.9959999918937683,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9939000010490417,"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/computer-science","display_name":"Computer science","score":0.723744809627533},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6957314610481262},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.6742876172065735},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.598723292350769},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5930913090705872},{"id":"https://openalex.org/keywords/watershed","display_name":"Watershed","score":0.5370489954948425},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.5155375003814697},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49586233496665955},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.48379725217819214},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4693053066730499},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4481741189956665},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.44536226987838745},{"id":"https://openalex.org/keywords/segmentation-based-object-categorization","display_name":"Segmentation-based object categorization","score":0.4453398883342743},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.43004241585731506},{"id":"https://openalex.org/keywords/division","display_name":"Division (mathematics)","score":0.41645267605781555},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.38357388973236084},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.21190407872200012},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15349242091178894}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.723744809627533},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6957314610481262},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.6742876172065735},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.598723292350769},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5930913090705872},{"id":"https://openalex.org/C150547873","wikidata":"https://www.wikidata.org/wiki/Q947851","display_name":"Watershed","level":2,"score":0.5370489954948425},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.5155375003814697},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49586233496665955},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.48379725217819214},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4693053066730499},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4481741189956665},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.44536226987838745},{"id":"https://openalex.org/C25694479","wikidata":"https://www.wikidata.org/wiki/Q7446278","display_name":"Segmentation-based object categorization","level":5,"score":0.4453398883342743},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.43004241585731506},{"id":"https://openalex.org/C60798267","wikidata":"https://www.wikidata.org/wiki/Q1226939","display_name":"Division (mathematics)","level":2,"score":0.41645267605781555},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.38357388973236084},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.21190407872200012},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15349242091178894},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2016.7730652","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2016.7730652","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","id":"https://metadata.un.org/sdg/15","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1965582803","https://openalex.org/W1976310976","https://openalex.org/W2041524230","https://openalex.org/W2103079830","https://openalex.org/W2112973039","https://openalex.org/W2124260943","https://openalex.org/W2133228628","https://openalex.org/W2151666808","https://openalex.org/W2159105546","https://openalex.org/W2165661463"],"related_works":["https://openalex.org/W2185902295","https://openalex.org/W2364730859","https://openalex.org/W2384989255","https://openalex.org/W2387253257","https://openalex.org/W2566648451","https://openalex.org/W2549765251","https://openalex.org/W404332504","https://openalex.org/W2074857711","https://openalex.org/W2125519506","https://openalex.org/W2903115243"],"abstract_inverted_index":{"Remote":[0],"sensing":[1,84],"image":[2,13],"segmentation":[3,133],"is":[4,111],"the":[5,9,39,48,55,58,108,120,131,136],"critical":[6],"process":[7,49],"in":[8,113,126],"workflow":[10],"of":[11,50,57,60,107],"object-based":[12],"analysis.":[14],"Recently,":[15],"region":[16,51,73,103,122],"merging":[17,74,123],"methods":[18],"have":[19],"attracted":[20],"growing":[21],"attention":[22],"because":[23],"they":[24],"are":[25],"able":[26],"to":[27,46,95,119],"utilize":[28],"more":[29],"features":[30],"than":[31],"spectral":[32,78],"signals":[33],"derived":[34],"from":[35],"initial":[36],"segments.":[37,64],"However,":[38],"existing":[40,121],"algorithms":[41],"commonly":[42],"use":[43],"fixed":[44],"parameters":[45],"control":[47],"merging,":[52],"which":[53],"limits":[54],"possibility":[56],"co-existence":[59],"large":[61],"and":[62,99,117],"small":[63],"To":[65],"address":[66],"this":[67],"issue,":[68],"we":[69],"propose":[70],"a":[71,114],"self-adapted":[72,101],"method,":[75,138],"based":[76],"on":[77],"angle":[79],"threshold,":[80],"toward":[81],"segmenting":[82],"remote":[83],"images.":[85],"This":[86],"method":[87,124,134],"involves":[88],"two":[89],"steps:":[90],"i)":[91],"multi-band":[92],"watershed":[93],"transformation":[94],"initiate":[96],"primitive":[97],"segments":[98],"ii)":[100],"threshold-based":[102],"merging.":[104],"The":[105,128],"performance":[106],"proposed":[109,132],"algorithm":[110],"evaluated":[112],"farmland":[115],"division":[116],"compared":[118],"implemented":[125],"SAGA.":[127],"results":[129],"reveal":[130],"outperforms":[135],"SAGA":[137],"as":[139],"indicated":[140],"by":[141],"its":[142],"lower":[143],"discrepancy":[144],"measure.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2026-02-13T13:36:01.753593","created_date":"2025-10-10T00:00:00"}