{"id":"https://openalex.org/W7124190909","doi":"https://doi.org/10.48550/arxiv.2601.08228","title":"Second-Generation Wavelet-inspired Tensor Product with Applications in Hyperspectral Imaging","display_name":"Second-Generation Wavelet-inspired Tensor Product with Applications in Hyperspectral Imaging","publication_year":2026,"publication_date":"2026-01-13","ids":{"openalex":"https://openalex.org/W7124190909","doi":"https://doi.org/10.48550/arxiv.2601.08228"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2601.08228","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.08228","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2601.08228","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107295625","display_name":"Aneesh Panchal","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Panchal, Aneesh","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5028105407","display_name":"Ratikanta Behera","orcid":"https://orcid.org/0000-0002-6237-5700"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Behera, Ratikanta","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5107295625"],"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/T12303","display_name":"Tensor decomposition and applications","score":0.7023000121116638,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12303","display_name":"Tensor decomposition and applications","score":0.7023000121116638,"subfield":{"id":"https://openalex.org/subfields/2605","display_name":"Computational Mathematics"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.14730000495910645,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.09059999883174896,"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/speedup","display_name":"Speedup","score":0.6983000040054321},{"id":"https://openalex.org/keywords/multiplication","display_name":"Multiplication (music)","score":0.6477000117301941},{"id":"https://openalex.org/keywords/deblurring","display_name":"Deblurring","score":0.6409000158309937},{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6158000230789185},{"id":"https://openalex.org/keywords/tensor","display_name":"Tensor (intrinsic definition)","score":0.5825999975204468},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5414000153541565},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.45969998836517334},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.44350001215934753},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.42800000309944153},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.42480000853538513}],"concepts":[{"id":"https://openalex.org/C68339613","wikidata":"https://www.wikidata.org/wiki/Q1549489","display_name":"Speedup","level":2,"score":0.6983000040054321},{"id":"https://openalex.org/C2780595030","wikidata":"https://www.wikidata.org/wiki/Q3860309","display_name":"Multiplication (music)","level":2,"score":0.6477000117301941},{"id":"https://openalex.org/C2777693668","wikidata":"https://www.wikidata.org/wiki/Q25053743","display_name":"Deblurring","level":5,"score":0.6409000158309937},{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6158000230789185},{"id":"https://openalex.org/C155281189","wikidata":"https://www.wikidata.org/wiki/Q3518150","display_name":"Tensor (intrinsic definition)","level":2,"score":0.5825999975204468},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5414000153541565},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5260000228881836},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44350001215934753},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4336000084877014},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.42800000309944153},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.42559999227523804},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.42480000853538513},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.41940000653266907},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35670000314712524},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3425000011920929},{"id":"https://openalex.org/C135252773","wikidata":"https://www.wikidata.org/wiki/Q1567213","display_name":"Inverse problem","level":2,"score":0.34209999442100525},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.33739998936653137},{"id":"https://openalex.org/C17349429","wikidata":"https://www.wikidata.org/wiki/Q1049914","display_name":"Matrix multiplication","level":3,"score":0.3240000009536743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C51255310","wikidata":"https://www.wikidata.org/wiki/Q1163016","display_name":"Tensor product","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C121927907","wikidata":"https://www.wikidata.org/wiki/Q1952516","display_name":"Multiresolution analysis","level":5,"score":0.2946000099182129},{"id":"https://openalex.org/C17020691","wikidata":"https://www.wikidata.org/wiki/Q139677","display_name":"Operator (biology)","level":5,"score":0.2937000095844269},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C207467116","wikidata":"https://www.wikidata.org/wiki/Q4385666","display_name":"Inverse","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.2824999988079071},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.2770000100135803},{"id":"https://openalex.org/C49766605","wikidata":"https://www.wikidata.org/wiki/Q207643","display_name":"Linear map","level":2,"score":0.2766999900341034},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.2750000059604645},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2667999863624573},{"id":"https://openalex.org/C9376300","wikidata":"https://www.wikidata.org/wiki/Q168817","display_name":"Algebraic number","level":2,"score":0.26339998841285706},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2624000012874603},{"id":"https://openalex.org/C139352143","wikidata":"https://www.wikidata.org/wiki/Q82571","display_name":"Linear algebra","level":2,"score":0.25}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2601.08228","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.08228","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2601.08228","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2601.08228","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":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0,143],"paper":[1],"introduces":[2],"the":[3,82,89,102,122,125,132,137,141],"$w$-product,":[4],"a":[5,66,146],"novel":[6],"wavelet-based":[7],"tensor":[8,29,38,162],"multiplication":[9,30],"scheme":[10],"leveraging":[11],"second-generation":[12],"wavelet":[13,159],"transforms":[14],"to":[15,65,71,100,112,136],"achieve":[16],"linear":[17],"transformation":[18],"complexity":[19],"while":[20],"preserving":[21],"essential":[22,94],"algebraic":[23],"properties.":[24,95],"The":[25],"$w$-product":[26,90,123],"outperforms":[27],"existing":[28],"approaches":[31],"by":[32,40],"enabling":[33],"fast":[34],"and":[35,43,77,91,124,164],"numerically":[36],"stable":[37],"decompositions":[39],"proposing":[41],"``$w$-svd''":[42],"its":[44,93],"sparse":[45],"variant":[46],"``sp-$w$-svd'',":[47],"for":[48,149],"efficient":[49],"low-rank":[50,59],"approximations":[51],"with":[52,74,116,131,153],"significantly":[53],"reduced":[54],"computational":[55],"costs.":[56],"Experiments":[57],"on":[58,88],"hyperspectral":[60,106],"image":[61,107,118],"reconstruction":[62],"demonstrate":[63,110],"up":[64,111],"$92.21$":[67],"times":[68,114],"speedup":[69,115],"compared":[70,135],"state-of-the-art":[72],"``$t$-svd'',":[73],"comparable":[75],"PSNR":[76],"SSIM":[78],"metrics.":[79],"We":[80],"discuss":[81],"Moore-Penrose":[83],"inverse":[84],"of":[85,140],"tensors":[86],"based":[87],"examine":[92],"Numerical":[96],"examples":[97],"are":[98],"provided":[99],"support":[101],"theoretical":[103],"results.":[104],"Then,":[105],"deblurring":[108],"experiments":[109],"$27.88$":[113],"improved":[117],"quality.":[119],"In":[120],"particular,":[121],"sp-$w$-product":[126],"exhibit":[127],"exponentially":[128],"increasing":[129],"acceleration":[130],"decomposition":[133],"level":[134],"traditional":[138],"approach":[139],"$t$-product.":[142],"work":[144],"provides":[145],"scalable":[147],"framework":[148],"multidimensional":[150],"data":[151],"analysis,":[152],"future":[154],"research":[155],"directions":[156],"including":[157],"adaptive":[158],"designs,":[160],"higher-order":[161],"extensions,":[163],"real-time":[165],"implementations.":[166]},"counts_by_year":[],"updated_date":"2026-01-15T23:21:31.212559","created_date":"2026-01-15T00:00:00"}
