{"id":"https://openalex.org/W7151952906","doi":"https://doi.org/10.48550/arxiv.2604.05742","title":"ASSR-Net: Anisotropic Structure-Aware and Spectrally Recalibrated Network for Hyperspectral Image Fusion","display_name":"ASSR-Net: Anisotropic Structure-Aware and Spectrally Recalibrated Network for Hyperspectral Image Fusion","publication_year":2026,"publication_date":"2026-04-07","ids":{"openalex":"https://openalex.org/W7151952906","doi":"https://doi.org/10.48550/arxiv.2604.05742"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.05742","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05742","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.05742","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018520101","display_name":"Qiya Song","orcid":"https://orcid.org/0000-0002-3115-0672"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Song, Qiya","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101948519","display_name":"Hongzhi Zhou","orcid":"https://orcid.org/0000-0003-4287-9095"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhou, Hongzhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102742197","display_name":"L.B. Tan","orcid":"https://orcid.org/0009-0007-8826-7867"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tan, Lishan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026156663","display_name":"Renwei Dian","orcid":"https://orcid.org/0000-0001-9197-6292"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dian, Renwei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133212730","display_name":"Shutao Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Shutao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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":false,"primary_topic":{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9857000112533569,"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"}},"topics":[{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9857000112533569,"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.005499999970197678,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.002899999963119626,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8878999948501587},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.54830002784729},{"id":"https://openalex.org/keywords/full-spectral-imaging","display_name":"Full spectral imaging","score":0.4812999963760376},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.4659000039100647},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.44850000739097595},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.44589999318122864},{"id":"https://openalex.org/keywords/anisotropy","display_name":"Anisotropy","score":0.4302999973297119},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41909998655319214},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.38260000944137573}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8878999948501587},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.656000018119812},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6029000282287598},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5684999823570251},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.54830002784729},{"id":"https://openalex.org/C78660771","wikidata":"https://www.wikidata.org/wiki/Q5508206","display_name":"Full spectral imaging","level":3,"score":0.4812999963760376},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.4659000039100647},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.44850000739097595},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.44600000977516174},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.44589999318122864},{"id":"https://openalex.org/C85725439","wikidata":"https://www.wikidata.org/wiki/Q466686","display_name":"Anisotropy","level":2,"score":0.4302999973297119},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41909998655319214},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.38260000944137573},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.3671000003814697},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34549999237060547},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C114700698","wikidata":"https://www.wikidata.org/wiki/Q2882278","display_name":"Spectral bands","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3140000104904175},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.30550000071525574},{"id":"https://openalex.org/C3232514","wikidata":"https://www.wikidata.org/wiki/Q7575196","display_name":"Spectral imaging","level":2,"score":0.30250000953674316},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.2976999878883362},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2856000065803528},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2728999853134155},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.26350000500679016},{"id":"https://openalex.org/C121475858","wikidata":"https://www.wikidata.org/wiki/Q2735911","display_name":"Spatial filter","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C100921725","wikidata":"https://www.wikidata.org/wiki/Q1650811","display_name":"Spatial frequency","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C176641082","wikidata":"https://www.wikidata.org/wiki/Q2446767","display_name":"Spectral signature","level":2,"score":0.2540999948978424},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.05742","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05742","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.05742","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.05742","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.5793672204017639}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Hyperspectral":[0,68],"image":[1],"fusion":[2,75,96],"aims":[3],"to":[4,127],"reconstruct":[5],"high-spatial-resolution":[6],"hyperspectral":[7],"images":[8],"(HR-HSI)":[9],"by":[10],"integrating":[11],"complementary":[12],"information":[13],"from":[14],"multi-source":[15],"inputs.":[16],"Despite":[17],"recent":[18],"progress,":[19],"existing":[20],"methods":[21],"still":[22],"face":[23],"two":[24],"critical":[25],"challenges:":[26],"(1)":[27],"inadequate":[28],"reconstruction":[29],"of":[30],"anisotropic":[31,78,107],"spatial":[32,40,80,108,155],"structures,":[33],"resulting":[34],"in":[35,132],"blurred":[36],"details":[37],"and":[38,42,63,83,158],"compromised":[39],"quality;":[41],"(2)":[43],"spectral":[44,51,86,115,125,130,138,159],"distortion":[45],"during":[46],"fusion,":[47],"which":[48],"hinders":[49],"fine-grained":[50],"representation.":[52],"To":[53],"address":[54],"these":[55],"issues,":[56],"we":[57],"propose":[58],"\\textbf{ASSR-Net}:":[59],"an":[60],"Anisotropic":[61],"Structure-Aware":[62],"Spectrally":[64],"Recalibrated":[65],"Network":[66],"for":[67],"Image":[69],"Fusion.":[70],"ASSR-Net":[71,148],"adopts":[72],"a":[73,93,114,124],"two-stage":[74],"strategy":[76],"comprising":[77],"structure-aware":[79],"enhancement":[81],"(ASSE)":[82],"hierarchical":[84],"prior-guided":[85],"calibration":[87],"(HPSC).":[88],"In":[89,110],"the":[90,111,119,133],"first":[91],"stage,":[92,113],"directional":[94],"perception":[95],"module":[97,117],"adaptively":[98],"captures":[99],"structural":[100],"features":[101],"along":[102],"multiple":[103],"orientations,":[104],"effectively":[105],"reconstructing":[106],"patterns.":[109],"second":[112],"recalibration":[116],"leverages":[118],"original":[120],"low-resolution":[121],"HSI":[122],"as":[123],"prior":[126],"explicitly":[128],"correct":[129],"deviations":[131],"fused":[134],"results,":[135],"thereby":[136],"enhancing":[137],"fidelity.":[139],"Extensive":[140],"experiments":[141],"on":[142],"various":[143],"benchmark":[144],"datasets":[145],"demonstrate":[146],"that":[147],"consistently":[149],"outperforms":[150],"state-of-the-art":[151],"methods,":[152],"achieving":[153],"superior":[154],"detail":[156],"preservation":[157],"consistency.":[160]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-09T00:00:00"}
