{"id":"https://openalex.org/W2537394792","doi":"https://doi.org/10.1109/tip.2016.2621410","title":"Depth Map Restoration From Undersampled Data","display_name":"Depth Map Restoration From Undersampled Data","publication_year":2016,"publication_date":"2016-10-25","ids":{"openalex":"https://openalex.org/W2537394792","doi":"https://doi.org/10.1109/tip.2016.2621410","mag":"2537394792","pmid":"https://pubmed.ncbi.nlm.nih.gov/27831871"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2016.2621410","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2016.2621410","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5008304477","display_name":"Srimanta Mandal","orcid":"https://orcid.org/0000-0003-3871-6621"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Srimanta Mandal","raw_affiliation_strings":["school of computing and electrical engineering, IIT Mandi, Mandi, India"],"affiliations":[{"raw_affiliation_string":"school of computing and electrical engineering, IIT Mandi, Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018647189","display_name":"Arnav Bhavsar","orcid":"https://orcid.org/0000-0003-2849-4375"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Arnav Bhavsar","raw_affiliation_strings":["school of computing and electrical engineering, IIT Mandi, Mandi, India"],"affiliations":[{"raw_affiliation_string":"school of computing and electrical engineering, IIT Mandi, Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025998364","display_name":"Anil Kumar Sao","orcid":"https://orcid.org/0000-0001-5316-5528"},"institutions":[{"id":"https://openalex.org/I9579091","display_name":"Indian Institute of Technology Mandi","ror":"https://ror.org/05r9r2f34","country_code":"IN","type":"education","lineage":["https://openalex.org/I9579091"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Anil Kumar Sao","raw_affiliation_strings":["school of computing and electrical engineering, IIT Mandi, Mandi, India"],"affiliations":[{"raw_affiliation_string":"school of computing and electrical engineering, IIT Mandi, Mandi, India","institution_ids":["https://openalex.org/I9579091"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5008304477"],"corresponding_institution_ids":["https://openalex.org/I9579091"],"apc_list":null,"apc_paid":null,"fwci":1.8371,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":{"value":0.90474432,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"26","issue":"1","first_page":"119","last_page":"134"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9998999834060669,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9983999729156494,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.9973000288009644,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/upsampling","display_name":"Upsampling","score":0.9409620761871338},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.8348177671432495},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.5479843020439148},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5189852118492126},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48073458671569824},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4763360619544983},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4758186936378479},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4750920534133911},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.4355219006538391},{"id":"https://openalex.org/keywords/classification-of-discontinuities","display_name":"Classification of discontinuities","score":0.43116405606269836},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4077448844909668},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3834525942802429},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2711976170539856},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.1064266562461853}],"concepts":[{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.9409620761871338},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.8348177671432495},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5479843020439148},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5189852118492126},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48073458671569824},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4763360619544983},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4758186936378479},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4750920534133911},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.4355219006538391},{"id":"https://openalex.org/C15627037","wikidata":"https://www.wikidata.org/wiki/Q541961","display_name":"Classification of discontinuities","level":2,"score":0.43116405606269836},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4077448844909668},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3834525942802429},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2711976170539856},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.1064266562461853},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2016.2621410","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2016.2621410","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:27831871","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/27831871","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6899999976158142,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1591116419","https://openalex.org/W1715998497","https://openalex.org/W1791560514","https://openalex.org/W1872406745","https://openalex.org/W1965735782","https://openalex.org/W1967027087","https://openalex.org/W1977948323","https://openalex.org/W1990365014","https://openalex.org/W1993133381","https://openalex.org/W1996126470","https://openalex.org/W2005441409","https://openalex.org/W2008523386","https://openalex.org/W2024427324","https://openalex.org/W2030300879","https://openalex.org/W2032240925","https://openalex.org/W2042729995","https://openalex.org/W2042802079","https://openalex.org/W2046333466","https://openalex.org/W2050834445","https://openalex.org/W2079351309","https://openalex.org/W2083031351","https://openalex.org/W2085181179","https://openalex.org/W2086470799","https://openalex.org/W2086835035","https://openalex.org/W2093117706","https://openalex.org/W2097074225","https://openalex.org/W2099712288","https://openalex.org/W2101131403","https://openalex.org/W2104599718","https://openalex.org/W2104600947","https://openalex.org/W2104974755","https://openalex.org/W2106403211","https://openalex.org/W2112421488","https://openalex.org/W2114147096","https://openalex.org/W2115706991","https://openalex.org/W2117865218","https://openalex.org/W2118273112","https://openalex.org/W2121058967","https://openalex.org/W2123782500","https://openalex.org/W2125188192","https://openalex.org/W2127441588","https://openalex.org/W2132219293","https://openalex.org/W2133255058","https://openalex.org/W2133665775","https://openalex.org/W2141568386","https://openalex.org/W2143516773","https://openalex.org/W2153388956","https://openalex.org/W2155479981","https://openalex.org/W2155830983","https://openalex.org/W2161516371","https://openalex.org/W2163398148","https://openalex.org/W2174855376","https://openalex.org/W2195231623","https://openalex.org/W2214189948","https://openalex.org/W2280455352","https://openalex.org/W2343141272","https://openalex.org/W2356493088","https://openalex.org/W2507755702","https://openalex.org/W2513083919","https://openalex.org/W2526999732","https://openalex.org/W2543980818","https://openalex.org/W3104072696","https://openalex.org/W3104720471","https://openalex.org/W4235713725","https://openalex.org/W4241716071","https://openalex.org/W6679506782","https://openalex.org/W6683660953","https://openalex.org/W6729410597"],"related_works":["https://openalex.org/W2795471480","https://openalex.org/W3176213335","https://openalex.org/W2104324080","https://openalex.org/W2520322935","https://openalex.org/W3005941135","https://openalex.org/W2086087387","https://openalex.org/W2027589961","https://openalex.org/W2140069086","https://openalex.org/W2155505427","https://openalex.org/W2537394792"],"abstract_inverted_index":{"Depth":[0],"map":[1,37,44,53,113,214,249],"sensed":[2],"by":[3,222],"low-cost":[4],"active":[5],"sensor":[6],"is":[7,156,172],"often":[8],"limited":[9],"in":[10,27,69,82,98,163,174,195],"resolution,":[11],"whereas":[12,73],"depth":[13,22,36,43,52,112,127,140,150,165,188,213,220,248],"information":[14,194],"achieved":[15],"from":[16,18,38,198,200,215],"structure":[17],"motion":[19],"or":[20,45],"sparse":[21,29,49,104,187,217],"scanning":[23],"techniques":[24],"may":[25],"result":[26],"a":[28,33,39,48,70,83,91,99,168,233],"point":[30],"cloud.":[31],"Achieving":[32],"high-resolution":[34],"(HR)":[35],"low":[40],"resolution":[41],"(LR)":[42],"densely":[46],"reconstructing":[47,211],"non-uniformly":[50,185,218],"sampled":[51,186,219],"are":[54,132,135],"fundamentally":[55],"similar":[56,201],"problems":[57],"with":[58,178],"different":[59],"types":[60],"of":[61,77,108,111,130,145,148,184,210,225,235,244],"upsampling":[62,68,81,147,180,183,229],"requirements.":[63],"The":[64],"first":[65],"problem":[66,78],"involves":[67],"uniform":[71,146,226],"grid,":[72],"the":[74,109,143,160,164,192,242],"second":[75],"type":[76],"requires":[79],"an":[80,120,152,207],"non-uniform":[84,228],"grid.":[85],"In":[86,142],"this":[87],"paper,":[88],"we":[89,190,204],"propose":[90],"new":[92],"approach":[93,116,246],"to":[94,137,176,240],"address":[95],"such":[96],"issues":[97],"unified":[100],"framework,":[101],"based":[102],"on":[103,125],"representation.":[105],"Unlike,":[106],"most":[107],"approaches":[110],"restoration,":[114],"our":[115,245],"does":[117],"not":[118],"require":[119],"HR":[121],"intensity":[122],"image.":[123],"Based":[124],"example":[126],"maps,":[128],"sub-dictionaries":[129],"exemplars":[131],"constructed,":[133],"and":[134,167,227,237],"used":[136,157],"restore":[138],"HR/dense":[139],"map.":[141],"case":[144],"LR":[149],"map,":[151,166,189],"edge":[153],"preserving":[154,159],"constraint":[155],"for":[158,247],"discontinuity":[161],"present":[162],"pyramidal":[169],"reconstruction":[170],"strategy":[171],"applied":[173],"order":[175],"deal":[177],"higher":[179],"factors.":[181],"For":[182],"compute":[191],"missing":[193],"local":[196],"patches":[197],"that":[199],"exemplars.":[202],"Furthermore,":[203],"also":[205],"suggest":[206],"alternative":[208],"method":[209],"dense":[212],"very":[216],"data":[221],"sequential":[223],"cascading":[224],"techniques.":[230],"We":[231],"provide":[232],"variety":[234],"qualitative":[236],"quantitative":[238],"results":[239],"demonstrate":[241],"efficacy":[243],"restoration.":[250]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}