{"id":"https://openalex.org/W6889736152","doi":"https://doi.org/10.26190/unsworks/16837","title":"Sequential Transmission of Remote Sensed Multi-temporal Images","display_name":"Sequential Transmission of Remote Sensed Multi-temporal Images","publication_year":2011,"publication_date":"2011-01-01","ids":{"openalex":"https://openalex.org/W6889736152","doi":"https://doi.org/10.26190/unsworks/16837"},"language":"en","primary_location":{"id":"pmh:oai:unsworks.unsw.edu.au:1959.4/53522","is_oa":true,"landing_page_url":"http://handle.unsw.edu.au/1959.4/53522","pdf_url":"http://handle.unsw.edu.au/1959.4/53522","source":{"id":"https://openalex.org/S4377196481","display_name":"UNSWorks (UNSW Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I31746571","host_organization_name":"UNSW Sydney","host_organization_lineage":["https://openalex.org/I31746571"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"type":"dissertation","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://handle.unsw.edu.au/1959.4/53522","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Mamun, Md. Al","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Mamun, Md. Al","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":0.9465000033378601,"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":0.9465000033378601,"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":0.009800000116229057,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.005900000222027302,"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/data-compression","display_name":"Data compression","score":0.6263999938964844},{"id":"https://openalex.org/keywords/terabyte","display_name":"Terabyte","score":0.5870000123977661},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.4722999930381775},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4713999927043915},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.4431999921798706},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.4429999887943268},{"id":"https://openalex.org/keywords/transmission","display_name":"Transmission (telecommunications)","score":0.4334000051021576},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.40939998626708984},{"id":"https://openalex.org/keywords/linear-regression","display_name":"Linear regression","score":0.3736000061035156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7210999727249146},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.6263999938964844},{"id":"https://openalex.org/C199683683","wikidata":"https://www.wikidata.org/wiki/Q8799","display_name":"Terabyte","level":2,"score":0.5870000123977661},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.4722999930381775},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4713999927043915},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4706999957561493},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.45010000467300415},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.4431999921798706},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.4429999887943268},{"id":"https://openalex.org/C761482","wikidata":"https://www.wikidata.org/wiki/Q118093","display_name":"Transmission (telecommunications)","level":2,"score":0.4334000051021576},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.40939998626708984},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.3736000061035156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C557945733","wikidata":"https://www.wikidata.org/wiki/Q389772","display_name":"Data transmission","level":2,"score":0.3562999963760376},{"id":"https://openalex.org/C163175372","wikidata":"https://www.wikidata.org/wiki/Q3339222","display_name":"Linear model","level":2,"score":0.3546000123023987},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.34389999508857727},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.32519999146461487},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.3239000141620636},{"id":"https://openalex.org/C180016635","wikidata":"https://www.wikidata.org/wiki/Q2712821","display_name":"Compression (physics)","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C131109320","wikidata":"https://www.wikidata.org/wiki/Q581012","display_name":"Linear prediction","level":2,"score":0.3156999945640564},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3125999867916107},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C153914771","wikidata":"https://www.wikidata.org/wiki/Q5227343","display_name":"Data reduction","level":2,"score":0.2696000039577484},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.26190000772476196},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.25929999351501465},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.2513999938964844}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:unsworks.unsw.edu.au:1959.4/53522","is_oa":true,"landing_page_url":"http://handle.unsw.edu.au/1959.4/53522","pdf_url":"http://handle.unsw.edu.au/1959.4/53522","source":{"id":"https://openalex.org/S4377196481","display_name":"UNSWorks (UNSW Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I31746571","host_organization_name":"UNSW Sydney","host_organization_lineage":["https://openalex.org/I31746571"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},{"id":"pmh:oai:unsworks.library.unsw.edu.au:1959.4/53522","is_oa":false,"landing_page_url":"http://hdl.handle.net/1959.4/53522","pdf_url":null,"source":{"id":"https://openalex.org/S4306401737","display_name":"UNSWorks (University of New South Wales, Sydney, Australia)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I40053085","host_organization_name":"Australian Defence Force Academy","host_organization_lineage":["https://openalex.org/I40053085"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"http://purl.org/coar/resource_type/c_db06"},{"id":"doi:10.26190/unsworks/16837","is_oa":true,"landing_page_url":"https://doi.org/10.26190/unsworks/16837","pdf_url":null,"source":{"id":"https://openalex.org/S7407053176","display_name":"University of New South Wales","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"thesis"}],"best_oa_location":{"id":"pmh:oai:unsworks.unsw.edu.au:1959.4/53522","is_oa":true,"landing_page_url":"http://handle.unsw.edu.au/1959.4/53522","pdf_url":"http://handle.unsw.edu.au/1959.4/53522","source":{"id":"https://openalex.org/S4377196481","display_name":"UNSWorks (UNSW Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I31746571","host_organization_name":"UNSW Sydney","host_organization_lineage":["https://openalex.org/I31746571"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W6889736152.pdf","grobid_xml":"https://content.openalex.org/works/W6889736152.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,335,351],"transmission":[1,35],"of":[2,23,50,117,123,149,182,196,303,322,327,357],"remote":[3,124],"sensed":[4,125],"images":[5,126,150,165,177],"across":[6],"communication":[7],"channels":[8],"has":[9],"become":[10],"very":[11],"expensive":[12],"due":[13],"to":[14,87,219,266,330],"recent":[15],"advances":[16],"in":[17,33,54,209,236,253,271],"satellite":[18],"technologies":[19],"that":[20,228,354],"generate":[21],"terabytes":[22],"data":[24,29,34,41,52,109,147,198,246,346],"every":[25,89,133,136],"day.":[26],"Therefore,":[27],"the":[28,48,55,70,92,95,115,121,145,164,176,194,210,221,224,231,268,272,304,311,323,332,355,358,364],"compression":[30,49,67,148,293,312],"techniques":[31,187],"involved":[32],"have":[36],"attracted":[37],"great":[38],"attention.":[39],"Current":[40],"reduction":[42],"methods":[43],"are":[44,104,106,167,199,204,282,299],"achieved":[45],"mainly":[46,169],"via":[47],"individual":[51],"set":[53],"spatial":[56,285],"and":[57,75,97,223,261,286,290,342],"spectral":[58,287],"domains.":[59],"In":[60],"this":[61,315],"thesis,":[62],"we":[63,212],"introduce":[64],"temporal":[65,71],"domain":[66,288],"by":[68,114,170],"exploiting":[69],"relationship":[72],"(including":[73],"correlation":[74],"mutual":[76,249],"information)":[77],"between":[78,94,152],"successive":[79,276],"images.":[80,277],"Rather":[81],"than":[82],"transmitting":[83],"a":[84,129,156,190,214,255,262,291],"complete":[85],"image":[86,99],"end-users":[88],"time,":[90],"only":[91],"differences":[93],"current":[96],"previous":[98],"data,":[100],"after":[101],"prediction":[102,142,191,280],"models":[103,143],"applied,":[105],"transmitted":[107],"for":[108,120,144,163,188,193,243,348],"updating.":[110],"This":[111,138],"is":[112,161,251,259,264,295,308,319,337,360],"motivated":[113],"requirement":[116],"many":[118],"applications":[119],"interpretation":[122],"gathered":[127],"over":[128],"regular":[130],"period,":[131],"e.g.,":[132],"day":[134],"or":[135,172],"week.":[137],"thesis":[139,316],"explores":[140],"three":[141,279],"effective":[146],"taken":[151],"two":[153],"dates.":[154],"Firstly,":[155],"single":[157,232],"linear":[158,216,233],"regression":[159,234],"model":[160,192,218,235,258],"developed":[162],"which":[166,254],"affected":[168],"system":[171],"environmental":[173],"noise.":[174],"When":[175],"do":[178],"experience":[179],"small":[180],"portions":[181],"real":[183,206,344],"changes,":[184],"outlier":[185],"removal":[186],"generating":[189],"majority":[195],"unchanged":[197],"proposed.":[200],"Secondly,":[201],"when":[202],"there":[203],"significant":[205],"changed":[207],"pixels":[208],"image,":[211],"propose":[213],"multiple":[215],"mixture":[217],"improve":[220],"regression,":[222],"experimental":[225],"results":[226,352],"show":[227,353],"it":[229,318],"outperforms":[230],"these":[237],"situations.":[238],"Also,":[239],"an":[240,320],"advanced":[241],"approach":[242],"managing":[244],"low-correlated":[245],"with":[247,284,301],"high":[248],"information":[250],"proposed":[252,365],"non-linear":[256],"elastic":[257],"developed,":[260],"codebook":[263],"generated":[265],"link":[267],"brightness":[269],"levels":[270],"most":[273],"closely":[274],"related":[275],"These":[278],"approaches":[281],"incorporated":[283],"predictions":[289],"4-D":[292],"framework":[294],"developed.":[296],"Their":[297],"performances":[298],"compared":[300],"those":[302],"JPEG2000":[305],"standard.":[306],"Entropy":[307],"used":[309],"as":[310,317],"measure":[313],"throughout":[314],"indicator":[321],"potentially":[324],"lowest":[325],"number":[326],"bits":[328],"required":[329],"transmit":[331],"compressed":[333],"image.":[334],"study":[336],"conducted":[338],"using":[339,363],"both":[340],"simulated":[341],"several":[343],"multispectral":[345],"sets":[347],"algorithm":[349],"evaluation.":[350],"entropy":[356],"residual":[359],"reduced":[361],"considerably":[362],"methods.":[366]},"counts_by_year":[],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}