{"id":"https://openalex.org/W2744786207","doi":"https://doi.org/10.1109/isit.2017.8007126","title":"Distributed coding of multispectral images","display_name":"Distributed coding of multispectral images","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2744786207","doi":"https://doi.org/10.1109/isit.2017.8007126","mag":"2744786207"},"language":"en","primary_location":{"id":"doi:10.1109/isit.2017.8007126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2017.8007126","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Symposium on Information Theory (ISIT)","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/A5044996415","display_name":"Maxim Goukhshtein","orcid":"https://orcid.org/0000-0002-0026-9670"},"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":"Maxim Goukhshtein","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034522188","display_name":"Petros T. Boufounos","orcid":"https://orcid.org/0000-0003-1369-0947"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Petros T. Boufounos","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023338067","display_name":"Toshiaki Koike\u2010Akino","orcid":"https://orcid.org/0000-0002-2578-5372"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Toshiaki Koike-Akino","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories (MERL), Cambridge, MA, USA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029182703","display_name":"Stark C. Draper","orcid":"https://orcid.org/0000-0001-8100-5599"},"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":"Stark C. Draper","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044996415"],"corresponding_institution_ids":["https://openalex.org/I185261750"],"apc_list":null,"apc_paid":null,"fwci":0.7203,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.68865394,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3230","last_page":"3234"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10901","display_name":"Advanced Data Compression 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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9914000034332275,"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":0.8124065399169922},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.7707537412643433},{"id":"https://openalex.org/keywords/distributed-source-coding","display_name":"Distributed source coding","score":0.651376485824585},{"id":"https://openalex.org/keywords/coding","display_name":"Coding (social sciences)","score":0.6471577882766724},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.6275172829627991},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.5821391344070435},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5720874071121216},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.5677964091300964},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5419801473617554},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.49729111790657043},{"id":"https://openalex.org/keywords/rate\u2013distortion-theory","display_name":"Rate\u2013distortion theory","score":0.43093717098236084},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3849828243255615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3390383720397949},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.2868613600730896},{"id":"https://openalex.org/keywords/variable-length-code","display_name":"Variable-length code","score":0.2268686294555664},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09376049041748047}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8124065399169922},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7707537412643433},{"id":"https://openalex.org/C200801453","wikidata":"https://www.wikidata.org/wiki/Q5283181","display_name":"Distributed source coding","level":4,"score":0.651376485824585},{"id":"https://openalex.org/C179518139","wikidata":"https://www.wikidata.org/wiki/Q5140297","display_name":"Coding (social sciences)","level":2,"score":0.6471577882766724},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.6275172829627991},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.5821391344070435},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5720874071121216},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.5677964091300964},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5419801473617554},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.49729111790657043},{"id":"https://openalex.org/C64185310","wikidata":"https://www.wikidata.org/wiki/Q843483","display_name":"Rate\u2013distortion theory","level":3,"score":0.43093717098236084},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3849828243255615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3390383720397949},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2868613600730896},{"id":"https://openalex.org/C60603091","wikidata":"https://www.wikidata.org/wiki/Q2981616","display_name":"Variable-length code","level":3,"score":0.2268686294555664},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09376049041748047},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isit.2017.8007126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isit.2017.8007126","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Symposium on Information Theory (ISIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W135467536","https://openalex.org/W1961240022","https://openalex.org/W1998208867","https://openalex.org/W2060256514","https://openalex.org/W2088214533","https://openalex.org/W2111394763","https://openalex.org/W2119667497","https://openalex.org/W2131573432","https://openalex.org/W2138256990","https://openalex.org/W2147861990","https://openalex.org/W2150412388","https://openalex.org/W2158770864","https://openalex.org/W2160390925","https://openalex.org/W2296616510","https://openalex.org/W2321331926","https://openalex.org/W2400237331","https://openalex.org/W2545750461","https://openalex.org/W2554591675","https://openalex.org/W4250955649"],"related_works":["https://openalex.org/W2546335063","https://openalex.org/W1554604567","https://openalex.org/W2545017178","https://openalex.org/W2141356835","https://openalex.org/W2159754152","https://openalex.org/W2153621579","https://openalex.org/W2149094627","https://openalex.org/W2121443236","https://openalex.org/W1776167994","https://openalex.org/W2887746482"],"abstract_inverted_index":{"Compression":[0],"of":[1,5,34,61,64,74,105],"multispectal":[2],"images":[3],"is":[4,85,98],"great":[6],"importance":[7],"in":[8,118],"an":[9],"environment":[10],"where":[11],"resources":[12],"such":[13],"as":[14],"computational":[15],"power":[16],"and":[17,51,66,91],"memory":[18],"are":[19],"scarce.":[20],"To":[21],"that":[22,37],"end,":[23],"we":[24],"propose":[25],"a":[26],"new":[27],"extremely":[28],"low-complexity":[29],"encoding":[30],"approach":[31],"for":[32],"compression":[33],"multispectral":[35],"images,":[36],"shifts":[38],"the":[39,42,56,62,72,75,89,103,106,109,119],"complexity":[40],"to":[41,70,81,87,92,101,124],"decoding.":[43],"Our":[44,112],"method":[45],"combines":[46],"principles":[47],"from":[48,108],"compressed":[49],"sensing":[50],"distributed":[52],"source":[53],"coding.":[54],"Specifically,":[55],"encoder":[57],"compressively":[58],"measures":[59],"blocks":[60],"band":[63],"interest":[65],"uses":[67],"syndrome":[68],"coding":[69,125],"encode":[71],"bitplanes":[73,90],"measurements.":[76,111],"The":[77,95],"decoder":[78],"has":[79],"access":[80],"side":[82,96],"information,":[83],"which":[84],"used":[86,100],"predict":[88],"decode":[93],"them.":[94],"information":[97],"also":[99],"guide":[102],"reconstruction":[104],"image":[107],"decoded":[110],"experimental":[113],"results":[114],"demonstrate":[115],"significant":[116],"improvement":[117],"rate-distortion":[120],"trade-off":[121],"when":[122],"compared":[123],"schemes":[126],"with":[127],"similar":[128],"complexity.":[129]},"counts_by_year":[{"year":2020,"cited_by_count":2},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
