{"id":"https://openalex.org/W2022677247","doi":"https://doi.org/10.1109/igarss.2014.6947101","title":"Effective hyperspectral image block compressed sensing using thress-dimensional wavelet transform","display_name":"Effective hyperspectral image block compressed sensing using thress-dimensional wavelet transform","publication_year":2014,"publication_date":"2014-07-01","ids":{"openalex":"https://openalex.org/W2022677247","doi":"https://doi.org/10.1109/igarss.2014.6947101","mag":"2022677247"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2014.6947101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6947101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100689398","display_name":"Ying Hou","orcid":"https://orcid.org/0000-0001-5888-8389"},"institutions":[{"id":"https://openalex.org/I110440473","display_name":"Xi'an University of Science and Technology","ror":"https://ror.org/046fkpt18","country_code":"CN","type":"education","lineage":["https://openalex.org/I110440473"]},{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Hou","raw_affiliation_strings":["School of Comm. and Information Engineering, Xi'an Univ. of Science and Technology","School of Computer Science, Northwestern Polytechnical Univ., Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Comm. and Information Engineering, Xi'an Univ. of Science and Technology","institution_ids":["https://openalex.org/I110440473"]},{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical Univ., Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103564469","display_name":"Zhang Yanning","orcid":"https://orcid.org/0009-0003-5848-3252"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanning Zhang","raw_affiliation_strings":["School of Computer Science, Northwestern Polytechnical Univ., Xi'an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Northwestern Polytechnical Univ., Xi'an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2973","last_page":"2976"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9998999834060669,"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":0.9998999834060669,"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/T12015","display_name":"Photoacoustic and Ultrasonic Imaging","score":0.9994999766349792,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.6774508953094482},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6449198722839355},{"id":"https://openalex.org/keywords/compressed-sensing","display_name":"Compressed sensing","score":0.5903781652450562},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5879130363464355},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.586268424987793},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5475550293922424},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5107951164245605},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5058343410491943},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5001010894775391},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.4907113313674927},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48047083616256714},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.47511348128318787},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4510580003261566},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3856150507926941},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32258039712905884},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2884882390499115}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.6774508953094482},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6449198722839355},{"id":"https://openalex.org/C124851039","wikidata":"https://www.wikidata.org/wiki/Q2665459","display_name":"Compressed sensing","level":2,"score":0.5903781652450562},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5879130363464355},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.586268424987793},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5475550293922424},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5107951164245605},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5058343410491943},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5001010894775391},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.4907113313674927},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48047083616256714},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.47511348128318787},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4510580003261566},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3856150507926941},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32258039712905884},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2884882390499115},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2014.6947101","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2014.6947101","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W38565172","https://openalex.org/W340244495","https://openalex.org/W1502593327","https://openalex.org/W1559556600","https://openalex.org/W2046074680","https://openalex.org/W2103115408","https://openalex.org/W2115706991","https://openalex.org/W2119667497","https://openalex.org/W2129812098","https://openalex.org/W2149931273","https://openalex.org/W2154304330","https://openalex.org/W2164452299","https://openalex.org/W2170885533","https://openalex.org/W2171783193","https://openalex.org/W2196956961","https://openalex.org/W2543013670","https://openalex.org/W2963322354","https://openalex.org/W3142290276","https://openalex.org/W4250955649","https://openalex.org/W4300263211","https://openalex.org/W6629927927","https://openalex.org/W6633495540","https://openalex.org/W6679164396"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2060875994","https://openalex.org/W3034375524","https://openalex.org/W4230131218","https://openalex.org/W2070598848","https://openalex.org/W2044184146","https://openalex.org/W4313014865","https://openalex.org/W2133587243","https://openalex.org/W2896778670"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"an":[3],"effective":[4],"block":[5],"compressed":[6,68],"sensing":[7,69],"algorithm":[8,63],"based":[9,35],"on":[10,36],"improved":[11,41],"noise":[12,42,50],"variance":[13,43],"estimation":[14,44],"method":[15,45],"is":[16],"proposed":[17,62],"for":[18],"hyperspectral":[19],"images.":[20],"The":[21,40],"reconstruction":[22,55],"process":[23],"adopts":[24],"the":[25,61],"iterative":[26],"projected":[27],"Landweber":[28],"and":[29,51],"soft-thresholding":[30],"bivariate":[31],"shrinkage":[32],"image":[33,54],"denoising":[34],"three-dimensional":[37],"wavelet":[38],"transform.":[39],"can":[46],"more":[47],"effectively":[48],"remove":[49],"achieve":[52],"better":[53],"quality.":[56],"Experimental":[57],"results":[58],"demonstrate":[59],"that":[60],"significantly":[64],"outperform":[65],"several":[66],"state-of-the-art":[67],"algorithms.":[70]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}