{"id":"https://openalex.org/W7126438349","doi":"https://doi.org/10.1145/3784713.3784724","title":"No-Reference Plane Image Quality Assessment Based on Differential Feature Fusion","display_name":"No-Reference Plane Image Quality Assessment Based on Differential Feature Fusion","publication_year":2025,"publication_date":"2025-11-14","ids":{"openalex":"https://openalex.org/W7126438349","doi":"https://doi.org/10.1145/3784713.3784724"},"language":null,"primary_location":{"id":"doi:10.1145/3784713.3784724","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784713.3784724","pdf_url":null,"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 2025 7th International Conference on Video, Signal and Image Processing","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3784713.3784724","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5032209786","display_name":"Yurui Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yurui Xie","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao, Shandong, China"],"raw_orcid":"https://orcid.org/0000-0003-0665-4411","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102518780","display_name":"Yongcan Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongcan Zhao","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao, Shandong, China"],"raw_orcid":"https://orcid.org/0009-0006-7203-6792","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5124643113","display_name":"Tianfeng Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianfeng Xia","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao, Shandong, China"],"raw_orcid":"https://orcid.org/0009-0006-5559-5082","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5124596078","display_name":"Lei Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["School of Information Science and Engineering, Shandong University, Qingdao, Shandong, China"],"raw_orcid":"https://orcid.org/0009-0006-2242-7269","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Shandong University, Qingdao, Shandong, China","institution_ids":["https://openalex.org/I154099455"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5032209786"],"corresponding_institution_ids":["https://openalex.org/I154099455"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.67989886,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"60","last_page":"66"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11165","display_name":"Image and Video Quality Assessment","score":0.8288999795913696,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.8288999795913696,"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":0.12080000340938568,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.007600000128149986,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/robustness","display_name":"Robustness (evolution)","score":0.6252999901771545},{"id":"https://openalex.org/keywords/image-quality","display_name":"Image quality","score":0.511900007724762},{"id":"https://openalex.org/keywords/human-visual-system-model","display_name":"Human visual system model","score":0.506600022315979},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5016999840736389},{"id":"https://openalex.org/keywords/image-plane","display_name":"Image plane","score":0.4912000000476837},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4779999852180481},{"id":"https://openalex.org/keywords/concatenation","display_name":"Concatenation (mathematics)","score":0.4702000021934509},{"id":"https://openalex.org/keywords/image-fusion","display_name":"Image fusion","score":0.4537000060081482},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.4140999913215637},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4083999991416931}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7436000108718872},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6323999762535095},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6252999901771545},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5271999835968018},{"id":"https://openalex.org/C55020928","wikidata":"https://www.wikidata.org/wiki/Q3813865","display_name":"Image quality","level":3,"score":0.511900007724762},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.506600022315979},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5016999840736389},{"id":"https://openalex.org/C120515352","wikidata":"https://www.wikidata.org/wiki/Q2564580","display_name":"Image plane","level":3,"score":0.4912000000476837},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4779999852180481},{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.4702000021934509},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.4537000060081482},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.4140999913215637},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4083999991416931},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.3822999894618988},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3792000114917755},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.3758000135421753},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.37130001187324524},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.3425999879837036},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.301800012588501},{"id":"https://openalex.org/C93226319","wikidata":"https://www.wikidata.org/wiki/Q193137","display_name":"Differential (mechanical device)","level":2,"score":0.2989000082015991},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2946000099182129},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.2944999933242798},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.28999999165534973},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C126422989","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature detection (computer vision)","level":4,"score":0.26739999651908875},{"id":"https://openalex.org/C173413354","wikidata":"https://www.wikidata.org/wiki/Q7049470","display_name":"Nonlinear distortion","level":4,"score":0.2651999890804291},{"id":"https://openalex.org/C106430172","wikidata":"https://www.wikidata.org/wiki/Q6002272","display_name":"Image restoration","level":4,"score":0.26030001044273376},{"id":"https://openalex.org/C63099799","wikidata":"https://www.wikidata.org/wiki/Q17147001","display_name":"Image texture","level":4,"score":0.2522999942302704},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.25099998712539673}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3784713.3784724","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784713.3784724","pdf_url":null,"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 2025 7th International Conference on Video, Signal and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3784713.3784724","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3784713.3784724","pdf_url":null,"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 2025 7th International Conference on Video, Signal and Image Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1987489060","https://openalex.org/W2141983208","https://openalex.org/W2148848374","https://openalex.org/W2161907179","https://openalex.org/W2171349048","https://openalex.org/W2322104612","https://openalex.org/W2562637781","https://openalex.org/W2752782242","https://openalex.org/W2768340063","https://openalex.org/W2884585870","https://openalex.org/W2905544033","https://openalex.org/W2963596827","https://openalex.org/W2964065910","https://openalex.org/W3034552520","https://openalex.org/W3035719652","https://openalex.org/W3123078562","https://openalex.org/W3194293177","https://openalex.org/W3204198763","https://openalex.org/W4210361933","https://openalex.org/W4403601500"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"the":[1,38,46,50,118,124,128,179,187,206,211],"human":[2,51],"visual":[3,52,65],"system":[4],"(HVS)":[5],"has":[6],"been":[7],"proven":[8],"very":[9],"important":[10],"in":[11],"no-reference":[12,75],"plane":[13,76],"image":[14,77,126,130,164],"quality":[15,78,144,165],"assessment.":[16],"Many":[17],"researchers":[18],"focus":[19],"their":[20],"studies":[21],"on":[22,82],"utilizing":[23],"critical":[24],"spatial":[25,56,114],"information":[26,57,60,109,185],"and":[27,34,58,103,113,127,150,158,182,208],"channel":[28,59,112],"features":[29,33,149,152,181],"to":[30,44,106,133,162],"model":[31],"local":[32,180],"global":[35,183],"structures.":[36],"However,":[37],"majority":[39],"of":[40,49,120,186,210],"existing":[41],"networks":[42],"fail":[43],"consider":[45],"distinct":[47],"characteristics":[48],"system,":[53],"which":[54,99,155,203],"processes":[55],"separately":[61],"when":[62],"dealing":[63],"with":[64],"data.":[66],"To":[67],"address":[68],"this":[69,139],"issue,":[70],"we":[71],"innovatively":[72],"propose":[73],"a":[74,88,141],"assessment":[79],"method":[80,175,191],"based":[81],"differential":[83],"feature":[84,108],"fusion":[85],"(NRIQA-DFF).":[86],"Firstly,":[87],"hybrid":[89],"parallel":[90],"attention":[91,160],"module":[92,161],"is":[93,131,153],"devised":[94],"for":[95,198],"constructing":[96],"recovery":[97],"networks,":[98],"incorporates":[100],"nonlinear":[101],"mapping":[102],"dilated":[104],"convolution":[105],"capture":[107,178],"across":[110],"both":[111],"dimensions":[115],"simultaneously.":[116],"Then,":[117],"difference":[119,136,151],"structural":[121,184],"similarity":[122],"between":[123],"distorted":[125],"pseudo-reference":[129],"calculated":[132],"obtain":[134],"perceptual":[135],"information.":[137],"On":[138],"basis,":[140],"novel":[142],"multi-branch":[143],"regression":[145],"network":[146],"fusing":[147],"reference":[148],"constructed,":[154],"combines":[156],"concatenation":[157],"an":[159],"predict":[163],"more":[166],"accurately.":[167],"The":[168,189],"experimental":[169],"results":[170],"show":[171],"that":[172],"our":[173],"proposed":[174,190,212],"can":[176],"effectively":[177],"image.":[188],"shows":[192],"superiority":[193],"over":[194],"other":[195],"related":[196],"methods":[197],"predicting":[199],"multiple":[200],"distortion":[201],"types,":[202],"also":[204],"demonstrates":[205],"robustness":[207],"generalization":[209],"method.":[213]},"counts_by_year":[],"updated_date":"2026-02-03T00:53:05.648605","created_date":"2026-02-02T00:00:00"}
