{"id":"https://openalex.org/W7134821017","doi":"https://doi.org/10.48550/arxiv.2603.07120","title":"Inter-Image Pixel Shuffling for Multi-focus Image Fusion","display_name":"Inter-Image Pixel Shuffling for Multi-focus Image Fusion","publication_year":2026,"publication_date":"2026-03-07","ids":{"openalex":"https://openalex.org/W7134821017","doi":"https://doi.org/10.48550/arxiv.2603.07120"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.07120","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5128658357","display_name":"Huangxing Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Huangxing","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128675190","display_name":"Rongrong Ma","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ma, Rongrong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5128684652","display_name":"Cheng Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Cheng","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.22978723,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.996999979019165,"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":0.996999979019165,"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/T11019","display_name":"Image Enhancement Techniques","score":0.0005000000237487257,"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/T13114","display_name":"Image Processing Techniques and Applications","score":0.00039999998989515007,"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/pixel","display_name":"Pixel","score":0.8669000267982483},{"id":"https://openalex.org/keywords/shuffling","display_name":"Shuffling","score":0.6615999937057495},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.5307999849319458},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.5142999887466431},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5019999742507935},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49630001187324524},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.45089998841285706},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.39259999990463257}],"concepts":[{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.8669000267982483},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7832000255584717},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6722999811172485},{"id":"https://openalex.org/C167927819","wikidata":"https://www.wikidata.org/wiki/Q1930567","display_name":"Shuffling","level":2,"score":0.6615999937057495},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6007000207901001},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.5307999849319458},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.5142999887466431},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5019999742507935},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49630001187324524},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.45089998841285706},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.39259999990463257},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3416000008583069},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.3260999917984009},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.3068999946117401},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2904999852180481},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2721000015735626},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.26750001311302185},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.25099998712539673}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.07120","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.07120","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.07120","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":"pmh:doi:10.48550/arxiv.2603.07120","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"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":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Multi-focus":[0],"image":[1,53,94,109,164,226],"fusion":[2,54,175,181,227],"aims":[3],"to":[4,50,73,147,160,212],"combine":[5],"multiple":[6],"partially":[7],"focused":[8,76,117,150],"images":[9],"into":[10],"a":[11,43,65,79,91,102,179],"single":[12],"all-in-focus":[13,163],"image.":[14],"Although":[15],"deep":[16],"learning":[17,159],"has":[18],"shown":[19],"promise":[20],"in":[21,125],"this":[22,87],"task,":[23],"its":[24],"effectiveness":[25],"is":[26,72,145],"often":[27],"limited":[28],"by":[29,165],"the":[30,62,70,75,107,116,126,149,170,185,194],"scarcity":[31],"of":[32,106,189,198],"suitable":[33],"training":[34,133,231],"data.":[35],"This":[36,202],"paper":[37],"introduces":[38],"Inter-image":[39],"Pixel":[40],"Shuffling":[41],"(IPS),":[42],"novel":[44],"method":[45],"that":[46,135,183,220],"allows":[47],"neural":[48,191],"networks":[49,192],"learn":[51],"multi-focus":[52,58,225,233],"without":[55,230],"requiring":[56],"actual":[57],"images.":[59,234],"IPS":[60,131,177,221],"reformulates":[61],"task":[63],"as":[64,97],"pixel-wise":[66],"classification":[67],"problem,":[68],"where":[69],"goal":[71],"identify":[74],"pixel":[77,80,151,156],"from":[78,90,101,152,169],"group":[81],"at":[82,121],"each":[83,153],"spatial":[84,123,137,207],"position.":[85],"In":[86],"method,":[88],"pixels":[89,100,120],"clear":[92],"optical":[93],"are":[95,110],"treated":[96],"focused,":[98],"while":[99,139],"low-pass":[103],"filtered":[104,129],"version":[105],"same":[108],"considered":[111],"defocused.":[112],"By":[113],"randomly":[114],"shuffling":[115],"and":[118,128,209],"defocused":[119],"identical":[122],"positions":[124],"original":[127],"images,":[130],"generates":[132],"data":[134],"preserves":[136],"structure":[138],"mixing":[140],"focus-defocus":[141],"information.":[142],"The":[143],"model":[144],"trained":[146],"select":[148],"spatially":[154],"aligned":[155],"group,":[157],"thus":[158],"reconstruct":[161],"an":[162],"aggregating":[166],"sharp":[167],"content":[168],"input.":[171],"To":[172],"further":[173],"enhance":[174],"quality,":[176],"adopts":[178],"cross-image":[180],"network":[182],"integrates":[184],"localized":[186],"representation":[187],"power":[188],"convolutional":[190],"with":[193],"long-range":[195],"modeling":[196],"capabilities":[197],"state":[199],"space":[200],"models.":[201],"design":[203],"effectively":[204],"leverages":[205],"both":[206],"detail":[208],"contextual":[210],"information":[211],"produce":[213],"high-quality":[214],"fused":[215],"results.":[216],"Experimental":[217],"results":[218],"indicate":[219],"significantly":[222],"outperforms":[223],"existing":[224],"methods,":[228],"even":[229],"on":[232]},"counts_by_year":[],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2026-03-11T00:00:00"}
