{"id":"https://openalex.org/W4416386023","doi":"https://doi.org/10.1145/3777465","title":"MCFINet: A Cost-Efficient Multi-Channel Feature Integration Network for Surface Scenarios Image Super-Resolution","display_name":"MCFINet: A Cost-Efficient Multi-Channel Feature Integration Network for Surface Scenarios Image Super-Resolution","publication_year":2025,"publication_date":"2025-11-19","ids":{"openalex":"https://openalex.org/W4416386023","doi":"https://doi.org/10.1145/3777465"},"language":"en","primary_location":{"id":"doi:10.1145/3777465","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3777465","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-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/A5101369241","display_name":"Liangcheng Zhao","orcid":"https://orcid.org/0000-0002-1117-0051"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liangcheng Zhao","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China","School of Mechatronic Engineering and Automation, Shanghai University, China"],"raw_orcid":"https://orcid.org/0000-0002-1117-0051","affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]},{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100661700","display_name":"Yueying Wang","orcid":"https://orcid.org/0000-0001-9737-6765"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yueying Wang","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China","School of Mechatronic Engineering and Automation, Shanghai University, China"],"raw_orcid":"https://orcid.org/0000-0001-9737-6765","affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]},{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054740535","display_name":"Yuhao Qing","orcid":"https://orcid.org/0009-0008-5921-5774"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuhao Qing","raw_affiliation_strings":["School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China","School of Mechatronic Engineering and Automation, Shanghai University, China"],"raw_orcid":"https://orcid.org/0009-0008-5921-5774","affiliations":[{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]},{"raw_affiliation_string":"School of Mechatronic Engineering and Automation, Shanghai University, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023724461","display_name":"Dan Zeng","orcid":"https://orcid.org/0000-0003-1300-1769"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dan Zeng","raw_affiliation_strings":["School of Communication and Information Engineering, Shanghai University, Shanghai, China","School of Communication and Information Engineering, Shanghai University, China"],"raw_orcid":"https://orcid.org/0000-0003-1300-1769","affiliations":[{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, Shanghai, China","institution_ids":["https://openalex.org/I113940042"]},{"raw_affiliation_string":"School of Communication and Information Engineering, Shanghai University, China","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029548002","display_name":"Li Xu","orcid":"https://orcid.org/0009-0007-6727-6190"},"institutions":[{"id":"https://openalex.org/I198645480","display_name":"North China University of Water Resources and Electric Power","ror":"https://ror.org/03acrzv41","country_code":"CN","type":"education","lineage":["https://openalex.org/I198645480"]},{"id":"https://openalex.org/I4210120238","display_name":"PowerChina (China)","ror":"https://ror.org/01varr368","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120238"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Xu","raw_affiliation_strings":["School of Electronic Engineering North China University of Water Resources and Electric Power, Zhengzhou, China","School of Electronic Engineering, North China University of Water Resources and Electric Power, China"],"raw_orcid":"https://orcid.org/0009-0007-6727-6190","affiliations":[{"raw_affiliation_string":"School of Electronic Engineering North China University of Water Resources and Electric Power, Zhengzhou, China","institution_ids":["https://openalex.org/I198645480"]},{"raw_affiliation_string":"School of Electronic Engineering, North China University of Water Resources and Electric Power, China","institution_ids":["https://openalex.org/I198645480","https://openalex.org/I4210120238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.084,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.79746791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":98},"biblio":{"volume":"22","issue":"1","first_page":"1","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":0.8784000277519226,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.8784000277519226,"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/T11019","display_name":"Image Enhancement Techniques","score":0.041099999099969864,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.017999999225139618,"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/block","display_name":"Block (permutation group theory)","score":0.6122999787330627},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5812000036239624},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.548799991607666},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5085999965667725},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4120999872684479},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3896999955177307},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.37790000438690186},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.3709999918937683}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.869700014591217},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6122999787330627},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5812000036239624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5733000040054321},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.548799991607666},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5085999965667725},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4120999872684479},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.37790000438690186},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3709999918937683},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.34880000352859497},{"id":"https://openalex.org/C127964446","wikidata":"https://www.wikidata.org/wiki/Q1092142","display_name":"Computational resource","level":3,"score":0.33739998936653137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3292999863624573},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.3287999927997589},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3273000121116638},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3271999955177307},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.325300008058548},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.32190001010894775},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.31779998540878296},{"id":"https://openalex.org/C113775141","wikidata":"https://www.wikidata.org/wiki/Q428691","display_name":"Computer engineering","level":1,"score":0.2867000102996826},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2718000113964081},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C33326189","wikidata":"https://www.wikidata.org/wiki/Q17092450","display_name":"Information integration","level":2,"score":0.26829999685287476},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2639999985694885},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.26159998774528503},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3777465","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3777465","pdf_url":null,"source":{"id":"https://openalex.org/S19610489","display_name":"ACM Transactions on Multimedia Computing Communications and Applications","issn_l":"1551-6857","issn":["1551-6857","1551-6865"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Multimedia Computing, Communications, and Applications","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2802250152","display_name":null,"funder_award_id":"62421004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1885185971","https://openalex.org/W1930824406","https://openalex.org/W2047920195","https://openalex.org/W2121227244","https://openalex.org/W2242218935","https://openalex.org/W2476548250","https://openalex.org/W2741137940","https://openalex.org/W2866634454","https://openalex.org/W2963372104","https://openalex.org/W2963470893","https://openalex.org/W2964101377","https://openalex.org/W2976718572","https://openalex.org/W3017083351","https://openalex.org/W3138516171","https://openalex.org/W3207918547","https://openalex.org/W4283721091","https://openalex.org/W4306174033","https://openalex.org/W4313156423","https://openalex.org/W4379620481","https://openalex.org/W4385525377","https://openalex.org/W4391074841","https://openalex.org/W4399487018","https://openalex.org/W4406526575","https://openalex.org/W4408092230","https://openalex.org/W4408100342"],"related_works":[],"abstract_inverted_index":{"Convolutional":[0],"Neural":[1],"Network":[2,50],"(CNN)":[3],"and":[4,33,66,88,114,156,164,180],"Vision":[5],"Transformer":[6],"(ViT)":[7],"have":[8],"revolutionized":[9],"the":[10,27,70,78,94,102,110,138,146,172,185],"field":[11],"of":[12,31,96],"image":[13],"super-resolution":[14],"(SR).":[15],"However,":[16],"their":[17,34,74],"complexity":[18,192],"poses":[19],"challenges":[20],"for":[21,121],"resource\u2014constrained":[22],"scenarios,":[23,127],"particularly":[24],"due":[25],"to":[26,53,171],"high":[28],"computational":[29,60,118],"demands":[30],"Transformers":[32],"excessive":[35],"reliance":[36],"on":[37,124,159,184],"global":[38,67],"information.":[39],"To":[40],"tackle":[41],"these":[42],"challenges,":[43],"we":[44,100,128],"propose":[45,129],"a":[46,130,150],"Multi-Channel":[47],"Feature":[48,80],"Integration":[49,81],"(MCFINet),":[51],"designed":[52,79],"maximize":[54],"input":[55],"pixel":[56],"utilization":[57],"while":[58,116,188],"minimizing":[59],"overhead.":[61],"It":[62],"integrates":[63],"both":[64,160],"local":[65,86],"features":[68,113],"within":[69],"channels,":[71],"thereby":[72],"exploiting":[73],"complementary":[75],"advantages.":[76],"First,":[77],"Block":[82,106],"(FIB)":[83],"effectively":[84],"captures":[85],"information":[87],"improves":[89],"visual":[90],"quality":[91],"by":[92,182,193],"enhancing":[93],"mapping":[95],"non-local":[97],"features.":[98],"Subsequently,":[99],"utilize":[101],"Adaptive":[103],"Channel":[104],"Fusion":[105],"(ACFB),":[107],"which":[108,135],"strengthens":[109],"interaction":[111],"between":[112,153],"channels":[115],"maintaining":[117],"efficiency.":[119],"Finally,":[120],"SR":[122],"task":[123],"resource-constrained":[125],"surface":[126,166],"more":[131],"suitable":[132],"pre-training":[133],"method,":[134],"further":[136],"boosts":[137],"model\u2019s":[139],"learning":[140],"ability.":[141],"Evaluation":[142],"results":[143],"indicate":[144],"that":[145],"proposed":[147],"MCFINet":[148,175],"achieves":[149],"better":[151],"balance":[152],"lightweight":[154],"design":[155],"high-quality":[157],"restoration":[158],"standard":[161],"evaluation":[162],"datasets":[163],"water":[165],"target":[167],"datasets.":[168],"Specifically,":[169],"compared":[170],"traditional":[173],"SwinIR-L,":[174],"reduces":[176],"model":[177,191],"training":[178],"time":[179],"runtime":[181],"12%":[183],"test":[186],"set,":[187],"also":[189],"decreasing":[190],"43%.":[194],"Our":[195],"codes":[196],"are":[197],"available":[198],"at":[199],"https://github.com/Lcasjz/MCFINet":[200],".":[201]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-25T15:57:00.446498","created_date":"2025-11-19T00:00:00"}
