{"id":"https://openalex.org/W1620726916","doi":"https://doi.org/10.1109/icacci.2015.7275948","title":"Spectral-spatial hyperspectral image compression based on measures of central tendency","display_name":"Spectral-spatial hyperspectral image compression based on measures of central tendency","publication_year":2015,"publication_date":"2015-08-01","ids":{"openalex":"https://openalex.org/W1620726916","doi":"https://doi.org/10.1109/icacci.2015.7275948","mag":"1620726916"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2015.7275948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2015.7275948","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","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/A5067166640","display_name":"Gayatri Deore","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gayatri Deore","raw_affiliation_strings":["Department of Electronics and Telecommunication, College of Engineering, Pune, India","Department of Electronics and Telecommunication, College of Engineering, Pune, INDIA"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunication, College of Engineering, Pune, India","institution_ids":[]},{"raw_affiliation_string":"Department of Electronics and Telecommunication, College of Engineering, Pune, INDIA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082055089","display_name":"Srividya Rajaraman","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Srividya Rajaraman","raw_affiliation_strings":["Department of Electronics and Telecommunication, College of Engineering, Pune, India","Department of Electronics and Telecommunication, College of Engineering, Pune, INDIA"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Telecommunication, College of Engineering, Pune, India","institution_ids":[]},{"raw_affiliation_string":"Department of Electronics and Telecommunication, College of Engineering, Pune, INDIA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018022464","display_name":"Rujuta Awate","orcid":null},"institutions":[{"id":"https://openalex.org/I145325580","display_name":"Deloitte (United States)","ror":"https://ror.org/03xkm6e60","country_code":"US","type":"company","lineage":["https://openalex.org/I145325580","https://openalex.org/I4210139068"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rujuta Awate","raw_affiliation_strings":["DeloitteConsulting, Mumbai, India","Deloitte Consulting, Mumbai, India"],"affiliations":[{"raw_affiliation_string":"DeloitteConsulting, Mumbai, India","institution_ids":[]},{"raw_affiliation_string":"Deloitte Consulting, Mumbai, India","institution_ids":["https://openalex.org/I145325580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020283367","display_name":"Saili Bakare","orcid":null},"institutions":[{"id":"https://openalex.org/I4210162508","display_name":"Whirlpool (India)","ror":"https://ror.org/05syv4032","country_code":"IN","type":"company","lineage":["https://openalex.org/I4210162508","https://openalex.org/I83790135"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Saili Bakare","raw_affiliation_strings":["Whirlpool of India Limited, Pune, India"],"affiliations":[{"raw_affiliation_string":"Whirlpool of India Limited, Pune, India","institution_ids":["https://openalex.org/I4210162508"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5067166640"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.03862517,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2012","issue":null,"first_page":"2226","last_page":"2232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9994000196456909,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9994000196456909,"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":0.9977999925613403,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.993399977684021,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.9528157711029053},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.7724838852882385},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.7313055992126465},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.6075528860092163},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.5326629877090454},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5104076266288757},{"id":"https://openalex.org/keywords/spectral-bands","display_name":"Spectral bands","score":0.4908981919288635},{"id":"https://openalex.org/keywords/quantization","display_name":"Quantization (signal processing)","score":0.48920249938964844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48704293370246887},{"id":"https://openalex.org/keywords/spectral-resolution","display_name":"Spectral resolution","score":0.4616794288158417},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.42801299691200256},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38876691460609436},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3638479709625244},{"id":"https://openalex.org/keywords/spectral-line","display_name":"Spectral line","score":0.16077378392219543},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.14014017581939697},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.12046244740486145}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.9528157711029053},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.7724838852882385},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.7313055992126465},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.6075528860092163},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.5326629877090454},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5104076266288757},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.4908981919288635},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.48920249938964844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48704293370246887},{"id":"https://openalex.org/C124967146","wikidata":"https://www.wikidata.org/wiki/Q3457898","display_name":"Spectral resolution","level":3,"score":0.4616794288158417},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.42801299691200256},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38876691460609436},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3638479709625244},{"id":"https://openalex.org/C4839761","wikidata":"https://www.wikidata.org/wiki/Q212111","display_name":"Spectral line","level":2,"score":0.16077378392219543},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.14014017581939697},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.12046244740486145},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2015.7275948","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2015.7275948","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1563253973","https://openalex.org/W1990474415","https://openalex.org/W2012968184","https://openalex.org/W2020187661","https://openalex.org/W2064410802","https://openalex.org/W2099050431","https://openalex.org/W2123038108","https://openalex.org/W2126575155","https://openalex.org/W2152595523","https://openalex.org/W4205318349","https://openalex.org/W6633675144","https://openalex.org/W6653751162","https://openalex.org/W6678637174"],"related_works":["https://openalex.org/W2911259277","https://openalex.org/W4386427838","https://openalex.org/W2024377932","https://openalex.org/W2107175121","https://openalex.org/W1978077614","https://openalex.org/W2889956472","https://openalex.org/W1982418987","https://openalex.org/W2799746630","https://openalex.org/W4390582117","https://openalex.org/W2090368006"],"abstract_inverted_index":{"Hyperspectral":[0],"images":[1,60,88],"have":[2],"become":[3],"an":[4],"active":[5],"research":[6],"topic":[7],"due":[8],"to":[9,50,69,75,129,135],"their":[10],"higher":[11,77],"spectral":[12,17,53,117],"resolution":[13],"provided":[14],"by":[15,22,112],"dense":[16],"sampling":[18],"at":[19],"each":[20],"pixel":[21],"a":[23,37,43,116],"number":[24],"of":[25,30,46,58,63,85,93,115,138],"narrow":[26],"and":[27,61,99,132],"contiguous":[28],"bands":[29,57],"wavelength.":[31],"In":[32],"this":[33,102,110],"paper,":[34],"we":[35],"propose":[36],"lossy":[38],"compression":[39],"approach":[40],"that":[41,83],"uses":[42],"novel":[44],"technique":[45],"applying":[47],"central":[48],"measures":[49],"exploit":[51,70],"inherent":[52],"correlation":[54,72],"in":[55,73,109],"consecutive":[56],"hyperspectral":[59,87],"use":[62,84,114],"vector":[64],"quantization":[65],"on":[66],"transform":[67],"coefficients":[68],"spatial":[71],"order":[74],"achieve":[76],"compression.":[78],"It":[79],"is":[80],"generally":[81],"perceived":[82],"compressed":[86],"may":[89],"affect":[90],"the":[91,113,139],"results":[92],"post-processing":[94],"stages":[95],"such":[96],"as":[97],"classification":[98],"unmixing,":[100],"however":[101],"possible":[103],"adverse":[104],"effect":[105],"has":[106],"been":[107],"considered":[108],"algorithm":[111],"distortion":[118],"measure,":[119],"Spectral":[120],"Angle":[121],"Mapper":[122],"(SAM)":[123],"along":[124],"with":[125],"conventional":[126],"Peak":[127],"Signal":[128],"Noise":[130],"Ratio":[131,134],"Compression":[133],"evaluate":[136],"performance":[137],"algorithm.":[140]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
