{"id":"https://openalex.org/W4390100429","doi":"https://doi.org/10.1145/3589132.3625638","title":"Saliency Driven Imagery Preprocessing for Efficient Compression - Industrial Paper","display_name":"Saliency Driven Imagery Preprocessing for Efficient Compression - Industrial Paper","publication_year":2023,"publication_date":"2023-11-13","ids":{"openalex":"https://openalex.org/W4390100429","doi":"https://doi.org/10.1145/3589132.3625638"},"language":"en","primary_location":{"id":"doi:10.1145/3589132.3625638","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625638","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625638","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625638","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059013699","display_name":"Justin Downes","orcid":"https://orcid.org/0000-0003-3257-3359"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Justin Downes","raw_affiliation_strings":["AWS, Herndon, United States"],"raw_orcid":"https://orcid.org/0000-0003-3257-3359","affiliations":[{"raw_affiliation_string":"AWS, Herndon, United States","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5093559179","display_name":"Sam Saltwick","orcid":"https://orcid.org/0009-0001-0643-063X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sam Saltwick","raw_affiliation_strings":["AWS, Herndon, United States"],"raw_orcid":"https://orcid.org/0009-0001-0643-063X","affiliations":[{"raw_affiliation_string":"AWS, Herndon, United States","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101995300","display_name":"Anthony Chen","orcid":"https://orcid.org/0009-0009-3665-6785"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Anthony Chen","raw_affiliation_strings":["AWS, Herndon, United States"],"raw_orcid":"https://orcid.org/0009-0009-3665-6785","affiliations":[{"raw_affiliation_string":"AWS, Herndon, United States","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1123,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.44053994,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9984999895095825,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9984999895095825,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.996399998664856,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9872999787330627,"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":0.8217853307723999},{"id":"https://openalex.org/keywords/lossy-compression","display_name":"Lossy compression","score":0.6338164806365967},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.6194865703582764},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6040538549423218},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5860933065414429},{"id":"https://openalex.org/keywords/satellite-imagery","display_name":"Satellite imagery","score":0.5266463756561279},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.5206343531608582},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.5192294716835022},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.5135617256164551},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5126992464065552},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.4649689495563507},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4315832555294037},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.41839611530303955},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.3389042019844055},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.324134886264801},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2658179700374603},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1030622124671936}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8217853307723999},{"id":"https://openalex.org/C165021410","wikidata":"https://www.wikidata.org/wiki/Q55564","display_name":"Lossy compression","level":2,"score":0.6338164806365967},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.6194865703582764},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6040538549423218},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5860933065414429},{"id":"https://openalex.org/C2778102629","wikidata":"https://www.wikidata.org/wiki/Q725252","display_name":"Satellite imagery","level":2,"score":0.5266463756561279},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.5206343531608582},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.5192294716835022},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.5135617256164551},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5126992464065552},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.4649689495563507},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4315832555294037},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.41839611530303955},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.3389042019844055},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.324134886264801},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2658179700374603},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1030622124671936},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3589132.3625638","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625638","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625638","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2601.17555","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.17555","pdf_url":"https://arxiv.org/pdf/2601.17555","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"doi:10.1145/3589132.3625638","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3589132.3625638","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3589132.3625638","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","score":0.5699999928474426,"display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4390100429.pdf","grobid_xml":"https://content.openalex.org/works/W4390100429.grobid-xml"},"referenced_works_count":25,"referenced_works":["https://openalex.org/W7317851","https://openalex.org/W1580440972","https://openalex.org/W1966446967","https://openalex.org/W2067187775","https://openalex.org/W2105581333","https://openalex.org/W2105722291","https://openalex.org/W2106219841","https://openalex.org/W2109863423","https://openalex.org/W2119153546","https://openalex.org/W2128620931","https://openalex.org/W2289860964","https://openalex.org/W2615178951","https://openalex.org/W2910101086","https://openalex.org/W2913884350","https://openalex.org/W3022548607","https://openalex.org/W3040744915","https://openalex.org/W3118843071","https://openalex.org/W3120432545","https://openalex.org/W3132886310","https://openalex.org/W3172088922","https://openalex.org/W3195300140","https://openalex.org/W3212245772","https://openalex.org/W4230291482","https://openalex.org/W4312573784","https://openalex.org/W4313891743"],"related_works":["https://openalex.org/W3210332869","https://openalex.org/W2547124190","https://openalex.org/W4210785996","https://openalex.org/W4327499886","https://openalex.org/W2385628723","https://openalex.org/W1680283075","https://openalex.org/W2751842002","https://openalex.org/W3180760233","https://openalex.org/W2096442341","https://openalex.org/W4210455546"],"abstract_inverted_index":{"The":[0],"compression":[1,127,135,165],"of":[2,12,14,36,49,55],"satellite":[3,38,140],"imagery":[4,114,158],"remains":[5],"an":[6],"important":[7,106],"research":[8],"area":[9],"as":[10],"hundreds":[11],"terabytes":[13],"images":[15],"are":[16,43,93],"collected":[17],"every":[18],"day,":[19],"which":[20],"drives":[21],"up":[22],"storage":[23],"and":[24,166],"bandwidth":[25],"costs.":[26],"Although":[27],"progress":[28],"has":[29],"been":[30],"made":[31],"in":[32,46,160],"increasing":[33],"the":[34,71,88],"resolution":[35],"these":[37],"images,":[39],"many":[40],"downstream":[41,164],"tasks":[42],"only":[44],"interested":[45],"small":[47],"regions":[48],"any":[50],"given":[51],"image.":[52,141],"These":[53],"areas":[54],"interest":[56],"vary":[57],"by":[58,100,118],"task":[59],"but,":[60],"once":[61],"known,":[62],"can":[63,97,121],"be":[64,98,122],"used":[65,123],"to":[66,103,130,151,156,162],"optimize":[67,163],"how":[68,113],"information":[69],"within":[70,136],"image":[72,77,90,134],"is":[73],"encoded.":[74],"Whereas":[75],"standard":[76],"encoding":[78,167],"methods,":[79],"even":[80],"those":[81],"optimized":[82],"for":[83],"remote":[84],"sensing,":[85],"work":[86,110],"on":[87,105],"whole":[89],"equally,":[91],"there":[92],"emerging":[94],"methods":[95],"that":[96,149],"guided":[99],"saliency":[101,119,154],"maps":[102,120],"focus":[104],"areas.":[107],"In":[108],"this":[109],"we":[111,143],"show":[112],"preprocessing":[115],"techniques":[116],"driven":[117],"with":[124],"traditional":[125],"lossy":[126],"coding":[128],"standards":[129],"create":[131],"variable":[132,145],"rate":[133],"a":[137],"single":[138],"large":[139],"Specifically,":[142],"use":[144],"sized":[146],"smoothing":[147],"kernels":[148],"map":[150],"different":[152],"quantized":[153],"levels":[155],"process":[157],"pixels":[159],"order":[161],"schemes.":[168]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}