{"id":"https://openalex.org/W4295127741","doi":"https://doi.org/10.1142/s0218126623500779","title":"A New Technique Based on AMID Using Adaptive Thresholding for Ultrasound Speckle Reduction","display_name":"A New Technique Based on AMID Using Adaptive Thresholding for Ultrasound Speckle Reduction","publication_year":2022,"publication_date":"2022-09-10","ids":{"openalex":"https://openalex.org/W4295127741","doi":"https://doi.org/10.1142/s0218126623500779"},"language":"en","primary_location":{"id":"doi:10.1142/s0218126623500779","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126623500779","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","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/A5084338403","display_name":"Bhawna Gupta","orcid":"https://orcid.org/0000-0003-3886-128X"},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Bhawna Gupta","raw_affiliation_strings":["ECE Department, Jaypee Institute of Information Technology, Sector 62, Noida, Uttar Pradesh, India"],"raw_orcid":"https://orcid.org/0000-0003-3886-128X","affiliations":[{"raw_affiliation_string":"ECE Department, Jaypee Institute of Information Technology, Sector 62, Noida, Uttar Pradesh, India","institution_ids":["https://openalex.org/I154970844"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109541336","display_name":"Vineet Khandelwal","orcid":null},"institutions":[{"id":"https://openalex.org/I154970844","display_name":"Jaypee Institute of Information Technology","ror":"https://ror.org/05sttyy11","country_code":"IN","type":"education","lineage":["https://openalex.org/I154970844"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Vineet Khandelwal","raw_affiliation_strings":["ECE Department, Jaypee Institute of Information Technology, Sector 62, Noida, Uttar Pradesh, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ECE Department, Jaypee Institute of Information Technology, Sector 62, Noida, Uttar Pradesh, India","institution_ids":["https://openalex.org/I154970844"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5084338403"],"corresponding_institution_ids":["https://openalex.org/I154970844"],"apc_list":null,"apc_paid":null,"fwci":0.0979,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.36510139,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"32","issue":"05","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"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":0.9998000264167786,"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/T11105","display_name":"Advanced Image Processing Techniques","score":0.9994000196456909,"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":0.9986000061035156,"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/thresholding","display_name":"Thresholding","score":0.7500224113464355},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6145155429840088},{"id":"https://openalex.org/keywords/peak-signal-to-noise-ratio","display_name":"Peak signal-to-noise ratio","score":0.584132194519043},{"id":"https://openalex.org/keywords/noise-reduction","display_name":"Noise reduction","score":0.5334164500236511},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5280545353889465},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4945621192455292},{"id":"https://openalex.org/keywords/speckle-noise","display_name":"Speckle noise","score":0.4885600507259369},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.45813751220703125},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.44826021790504456},{"id":"https://openalex.org/keywords/signal-to-noise-ratio","display_name":"Signal-to-noise ratio (imaging)","score":0.43074917793273926},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4253259599208832},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.395624577999115},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38601166009902954},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11833477020263672}],"concepts":[{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.7500224113464355},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6145155429840088},{"id":"https://openalex.org/C154579607","wikidata":"https://www.wikidata.org/wiki/Q3373850","display_name":"Peak signal-to-noise ratio","level":3,"score":0.584132194519043},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.5334164500236511},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5280545353889465},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4945621192455292},{"id":"https://openalex.org/C180940675","wikidata":"https://www.wikidata.org/wiki/Q7575045","display_name":"Speckle noise","level":3,"score":0.4885600507259369},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.45813751220703125},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.44826021790504456},{"id":"https://openalex.org/C13944312","wikidata":"https://www.wikidata.org/wiki/Q7512748","display_name":"Signal-to-noise ratio (imaging)","level":2,"score":0.43074917793273926},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4253259599208832},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.395624577999115},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38601166009902954},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11833477020263672}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218126623500779","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218126623500779","pdf_url":null,"source":{"id":"https://openalex.org/S167602672","display_name":"Journal of Circuits Systems and Computers","issn_l":"0218-1266","issn":["0218-1266","1793-6454"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Circuits, Systems and Computers","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W576506256","https://openalex.org/W1510751240","https://openalex.org/W1540834342","https://openalex.org/W1627054999","https://openalex.org/W1942378940","https://openalex.org/W1977936825","https://openalex.org/W1980160456","https://openalex.org/W1989696065","https://openalex.org/W2006663170","https://openalex.org/W2031488994","https://openalex.org/W2052531542","https://openalex.org/W2070626824","https://openalex.org/W2081359092","https://openalex.org/W2084212442","https://openalex.org/W2094792702","https://openalex.org/W2096413230","https://openalex.org/W2110206939","https://openalex.org/W2111595891","https://openalex.org/W2112212587","https://openalex.org/W2113952909","https://openalex.org/W2117294245","https://openalex.org/W2130094715","https://openalex.org/W2130622335","https://openalex.org/W2132680427","https://openalex.org/W2133665775","https://openalex.org/W2146842127","https://openalex.org/W2150134853","https://openalex.org/W2160637922","https://openalex.org/W2161811007","https://openalex.org/W2170271483","https://openalex.org/W2257791676","https://openalex.org/W2677852072","https://openalex.org/W2889926833","https://openalex.org/W2913559493","https://openalex.org/W2945177640","https://openalex.org/W2954537798","https://openalex.org/W2990734975","https://openalex.org/W2995221098","https://openalex.org/W3112211854","https://openalex.org/W3143299112","https://openalex.org/W3201924884"],"related_works":["https://openalex.org/W2162516678","https://openalex.org/W1986344865","https://openalex.org/W2069178059","https://openalex.org/W2105436453","https://openalex.org/W2130027519","https://openalex.org/W3175931863","https://openalex.org/W2002535156","https://openalex.org/W2899236994","https://openalex.org/W4322577585","https://openalex.org/W2088472716"],"abstract_inverted_index":{"A":[0],"new":[1],"technique":[2,110],"based":[3],"on":[4,114],"adaptive":[5,11,58,84,87,91],"multi-resolution":[6],"image":[7,25,35,67,106],"decomposition":[8,85],"(AMID)":[9],"using":[10,48],"thresholding":[12,59,88],"for":[13,169,189],"ultrasound":[14,120,191],"speckle":[15],"reduction":[16],"has":[17],"been":[18],"proposed":[19,109,134],"in":[20,103,144,177],"this":[21],"paper.":[22],"The":[23,34,51,66,108,128,172],"noisy":[24],"is":[26,36,60,68,112],"first":[27],"filtered":[28,56],"to":[29,42,62,76,92],"reduce":[30],"large":[31],"multiplicative":[32],"noise.":[33],"then":[37],"log-transformed":[38],"before":[39],"decomposing":[40],"it":[41,90],"its":[43],"approximation":[44,52],"and":[45,95,165,185],"detailed":[46],"coefficients":[47,53,75],"AMID":[49],"algorithm.":[50],"are":[54],"appropriately":[55],"while":[57],"applied":[61],"the":[63,73,78,100,104,123,133,140],"detail":[64],"coefficients.":[65],"reconstructed":[69],"back":[70],"from":[71],"all":[72],"modified":[74],"obtain":[77],"denoised":[79,105],"image.":[80],"This":[81],"method":[82],"combining":[83],"with":[86,122],"makes":[89],"both":[93],"signal":[94],"noise":[96,124],"components,":[97],"thereby":[98],"retaining":[99],"edge":[101,147],"details":[102],"effectively.":[107],"performance":[111,138,176],"tested":[113],"synthetic":[115,170],"as":[116,118],"well":[117],"real":[119,190],"images":[121],"of":[125,146,155,179,182],"different":[126],"variances.":[127],"experimental":[129],"results":[130],"show":[131],"that":[132],"algorithm":[135,173],"gives":[136,174],"better":[137,175],"than":[139],"other":[141],"state-of-the-art":[142],"methods":[143],"terms":[145,178],"keeping":[148],"index":[149],"(EKI),":[150],"correlation":[151],"coefficient":[152],"(CC),":[153],"figure":[154],"merit":[156],"(FOM),":[157],"peak":[158],"signal-to-noise":[159,166],"ratio":[160,167,187],"(PSNR),":[161],"structural":[162],"similarity":[163],"(SSIM)":[164],"(SNR)":[168],"images.":[171,192],"equivalent":[180],"number":[181],"looks":[183],"(ENL)":[184],"mean-to-variance":[186],"(MVR)":[188]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}