{"id":"https://openalex.org/W2771275843","doi":"https://doi.org/10.1109/ssd.2017.8166932","title":"Image denoising using wave atom transform","display_name":"Image denoising using wave atom transform","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2771275843","doi":"https://doi.org/10.1109/ssd.2017.8166932","mag":"2771275843"},"language":"en","primary_location":{"id":"doi:10.1109/ssd.2017.8166932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd.2017.8166932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 14th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","raw_type":"proceedings-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/A5069149575","display_name":"Khelil Seif Eddine","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Khelil Seif Eddine","raw_affiliation_strings":["ENSIT, University of Tunis, Tunis, Tunisia"],"affiliations":[{"raw_affiliation_string":"ENSIT, University of Tunis, Tunis, Tunisia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065753894","display_name":"Hassene Seddik","orcid":"https://orcid.org/0000-0003-0848-8285"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Seddik Hassene","raw_affiliation_strings":["ENSIT, University of Tunis, Tunis, Tunisia"],"affiliations":[{"raw_affiliation_string":"ENSIT, University of Tunis, Tunis, Tunisia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5069149575"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.17421677,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"35","issue":null,"first_page":"450","last_page":"455"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9995999932289124,"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9995999932289124,"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":0.9973000288009644,"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/T10271","display_name":"Seismic Imaging and Inversion Techniques","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/1908","display_name":"Geophysics"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.710146427154541},{"id":"https://openalex.org/keywords/curvelet","display_name":"Curvelet","score":0.5684623718261719},{"id":"https://openalex.org/keywords/s-transform","display_name":"S transform","score":0.5411526560783386},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.531376302242279},{"id":"https://openalex.org/keywords/harmonic-wavelet-transform","display_name":"Harmonic wavelet transform","score":0.5098485350608826},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4122138023376465},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3960159420967102},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.376424103975296},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.36961501836776733},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3673822283744812},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.333492636680603},{"id":"https://openalex.org/keywords/wavelet-packet-decomposition","display_name":"Wavelet packet decomposition","score":0.3052675724029541}],"concepts":[{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.710146427154541},{"id":"https://openalex.org/C131720326","wikidata":"https://www.wikidata.org/wiki/Q5196075","display_name":"Curvelet","level":4,"score":0.5684623718261719},{"id":"https://openalex.org/C99234102","wikidata":"https://www.wikidata.org/wiki/Q7395403","display_name":"S transform","level":5,"score":0.5411526560783386},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.531376302242279},{"id":"https://openalex.org/C1109138","wikidata":"https://www.wikidata.org/wiki/Q3280930","display_name":"Harmonic wavelet transform","level":5,"score":0.5098485350608826},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4122138023376465},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3960159420967102},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.376424103975296},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.36961501836776733},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3673822283744812},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.333492636680603},{"id":"https://openalex.org/C155777637","wikidata":"https://www.wikidata.org/wiki/Q2736187","display_name":"Wavelet packet decomposition","level":4,"score":0.3052675724029541}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ssd.2017.8166932","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssd.2017.8166932","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 14th International Multi-Conference on Systems, Signals &amp; Devices (SSD)","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":10,"referenced_works":["https://openalex.org/W1793403863","https://openalex.org/W2069912449","https://openalex.org/W2071019168","https://openalex.org/W2162547327","https://openalex.org/W2168141504","https://openalex.org/W2328691931","https://openalex.org/W2353208499","https://openalex.org/W2365508492","https://openalex.org/W6638426394","https://openalex.org/W6705514940"],"related_works":["https://openalex.org/W2384626809","https://openalex.org/W2085792030","https://openalex.org/W2103042932","https://openalex.org/W2390879839","https://openalex.org/W1967182499","https://openalex.org/W1588899229","https://openalex.org/W1976022598","https://openalex.org/W2360367699","https://openalex.org/W2378148381","https://openalex.org/W2135084094"],"abstract_inverted_index":{"The":[0],"image":[1,79,97,106],"usually":[2],"has":[3,57,90,139],"different":[4],"kinds":[5],"of":[6,15,24,44,78,85,146],"noises":[7],"which":[8,52,89],"are":[9],"not":[10],"easily":[11],"removed":[12],"in":[13,96],"process":[14],"receiving,":[16],"coding":[17],"and":[18,46,48,71,87,152],"transmission.":[19],"Wave":[20,116],"atoms":[21],"is":[22,33,67],"one":[23],"the":[25,42,76,127,134,144],"new":[26,103,120],"geometric":[27],"multiscale-multidirectional":[28],"transform,":[29,37],"after":[30],"1999":[31],"that":[32,62,133],"based":[34,111],"on":[35,112],"wavelet":[36,70],"whose":[38],"structural":[39],"elements":[40],"involve":[41],"parameters":[43],"dimension":[45],"location,":[47],"orientation":[49,59],"parameter":[50],"more,":[51],"let":[53],"wave":[54,64,113,136],"atom":[55,65,114,117,137],"transform":[56,66,138],"good":[58],"characteristic.":[60],"For":[61],"reason,":[63],"better":[68,155],"than":[69,126],"even":[72],"curvelet":[73],"transform.":[74,115,129],"In":[75],"expression":[77],"edge,":[80],"such":[81],"as":[82],"geometry":[83],"characteristic":[84],"curve":[86],"beeline,":[88],"previously":[91],"obtained":[92],"excellent":[93],"research":[94],"results":[95,131],"denoising.":[98],"This":[99],"paper":[100],"introduced":[101],"a":[102,119,123,154],"method":[104],"for":[105,142],"de-noising":[107],"by":[108],"coefficient":[109],"thresholding":[110],"proposes":[118],"representation":[121],"have":[122],"higher":[124],"performance":[125],"other":[128],"Experiments":[130],"indicate":[132],"improved":[135],"abroad":[140],"future":[141],"eliminating":[143],"noise":[145],"images.":[147],"It":[148],"remains":[149],"edges":[150],"efficiently,":[151],"offers":[153],"visual":[156],"effect.":[157]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
