{"id":"https://openalex.org/W4220693531","doi":"https://doi.org/10.1142/s0218001422540064","title":"DWT Lifting Scheme for Image Compression with Cordic-Enhanced Operation","display_name":"DWT Lifting Scheme for Image Compression with Cordic-Enhanced Operation","publication_year":2022,"publication_date":"2022-03-30","ids":{"openalex":"https://openalex.org/W4220693531","doi":"https://doi.org/10.1142/s0218001422540064"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001422540064","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422540064","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"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":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5006027551","display_name":"M I Anju","orcid":null},"institutions":[{"id":"https://openalex.org/I33585257","display_name":"Anna University, Chennai","ror":"https://ror.org/01qhf1r47","country_code":"IN","type":"education","lineage":["https://openalex.org/I33585257"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"M. I. Anju","raw_affiliation_strings":["Department of Electronics and Communication Engineering, Anna University, Guindy, Chennai, Tamilnadu, 600025, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, Anna University, Guindy, Chennai, Tamilnadu, 600025, India","institution_ids":["https://openalex.org/I33585257"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5018760421","display_name":"J. Mohan","orcid":null},"institutions":[{"id":"https://openalex.org/I145286018","display_name":"SRM Institute of Science and Technology","ror":"https://ror.org/050113w36","country_code":"IN","type":"education","lineage":["https://openalex.org/I145286018"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"J. Mohan","raw_affiliation_strings":["Department of Electronics and Communication Engineering, SRM Valliammai Engineering College, Kattankulathur, Tamilnadu, 603203, India"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Communication Engineering, SRM Valliammai Engineering College, Kattankulathur, Tamilnadu, 603203, India","institution_ids":["https://openalex.org/I145286018"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5006027551"],"corresponding_institution_ids":["https://openalex.org/I33585257"],"apc_list":null,"apc_paid":null,"fwci":0.2012,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.44379426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"36","issue":"04","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","score":1.0,"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/T10901","display_name":"Advanced Data Compression Techniques","score":1.0,"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/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/T11034","display_name":"Digital Filter Design and Implementation","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/lifting-scheme","display_name":"Lifting scheme","score":0.6506510972976685},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.6395052075386047},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5782949328422546},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5759625434875488},{"id":"https://openalex.org/keywords/image-compression","display_name":"Image compression","score":0.527271568775177},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.5165501832962036},{"id":"https://openalex.org/keywords/cordic","display_name":"CORDIC","score":0.49653345346450806},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4498429298400879},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4345128536224365},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.42395079135894775},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.3466901183128357},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.286050021648407},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2633952498435974},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.1794348955154419},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.16340354084968567},{"id":"https://openalex.org/keywords/computer-hardware","display_name":"Computer hardware","score":0.10404461622238159}],"concepts":[{"id":"https://openalex.org/C199550912","wikidata":"https://www.wikidata.org/wiki/Q3238415","display_name":"Lifting scheme","level":5,"score":0.6506510972976685},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.6395052075386047},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5782949328422546},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5759625434875488},{"id":"https://openalex.org/C13481523","wikidata":"https://www.wikidata.org/wiki/Q412438","display_name":"Image compression","level":4,"score":0.527271568775177},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.5165501832962036},{"id":"https://openalex.org/C58870171","wikidata":"https://www.wikidata.org/wiki/Q116076","display_name":"CORDIC","level":3,"score":0.49653345346450806},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4498429298400879},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4345128536224365},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.42395079135894775},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.3466901183128357},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.286050021648407},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2633952498435974},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.1794348955154419},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.16340354084968567},{"id":"https://openalex.org/C9390403","wikidata":"https://www.wikidata.org/wiki/Q3966","display_name":"Computer hardware","level":1,"score":0.10404461622238159},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C42935608","wikidata":"https://www.wikidata.org/wiki/Q190411","display_name":"Field-programmable gate array","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001422540064","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001422540064","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"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":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","id":"https://metadata.un.org/sdg/14","score":0.6499999761581421}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W178445001","https://openalex.org/W1973378935","https://openalex.org/W1974267159","https://openalex.org/W1981516546","https://openalex.org/W2036304367","https://openalex.org/W2060324068","https://openalex.org/W2087345335","https://openalex.org/W2092347923","https://openalex.org/W2110390205","https://openalex.org/W2130422497","https://openalex.org/W2130429346","https://openalex.org/W2163625959","https://openalex.org/W2166135038","https://openalex.org/W2275053611","https://openalex.org/W2290152521","https://openalex.org/W2290883490","https://openalex.org/W2342741070","https://openalex.org/W2462225876","https://openalex.org/W2496231329","https://openalex.org/W2562807428","https://openalex.org/W2571711249","https://openalex.org/W2584403383","https://openalex.org/W2593670284","https://openalex.org/W2766360885","https://openalex.org/W2767335027","https://openalex.org/W2772807769","https://openalex.org/W2789561488","https://openalex.org/W2800262624","https://openalex.org/W2889827362","https://openalex.org/W2890790898","https://openalex.org/W2905821319","https://openalex.org/W2907270715","https://openalex.org/W2914628419","https://openalex.org/W2915863155","https://openalex.org/W2936234519","https://openalex.org/W2941292665","https://openalex.org/W2964248800","https://openalex.org/W2964917347","https://openalex.org/W3043381494"],"related_works":["https://openalex.org/W1669404982","https://openalex.org/W2052163925","https://openalex.org/W3200179225","https://openalex.org/W2059234650","https://openalex.org/W2949031990","https://openalex.org/W2534725092","https://openalex.org/W2906192557","https://openalex.org/W2367020991","https://openalex.org/W1588899229","https://openalex.org/W2336053056"],"abstract_inverted_index":{"This":[0],"paper":[1,116],"proposes":[2],"an":[3,52],"innovative":[4,53,102],"image":[5],"compression":[6],"scheme":[7],"by":[8],"utilizing":[9],"the":[10,23,30,44,64,87,91,111,126,138,141],"Adaptive":[11],"Discrete":[12],"Wavelet":[13],"Transform-based":[14],"Lifting":[15],"Scheme":[16],"(ADWT-LS).":[17],"The":[18,83],"most":[19,65],"important":[20,66],"feature":[21],"of":[22,89,140],"proposed":[24,84,142],"DWT":[25],"lifting":[26,54],"method":[27],"is":[28,63,69,105,144],"splitting":[29],"low-pass":[31],"and":[32,37,95],"high-pass":[33],"filters":[34],"into":[35,47],"upper":[36],"lower":[38],"triangular":[39],"matrices.":[40],"It":[41],"also":[42],"converts":[43],"filter":[45],"execution":[46],"banded":[48],"matrix":[49],"multiplications":[50],"with":[51,57],"factorization":[55],"presented":[56],"fine-tuned":[58],"parameters.":[59],"Further,":[60],"optimal":[61],"tuning":[62],"contribution":[67],"that":[68,122],"achieved":[70],"via":[71],"a":[72,118],"new":[73],"hybrid":[74],"algorithm":[75,85],"known":[76],"as":[77,131,133],"Lioness-Integrated":[78],"Whale":[79,96],"Optimization":[80,97],"Algorithm":[81,93,98],"(LI-WOA).":[82],"hybridizes":[86],"concepts":[88],"both":[90],"Lion":[92],"(LA)":[94],"(WOA).":[99],"In":[100],"addition,":[101],"cosine":[103],"evaluation":[104],"initiated":[106],"in":[107],"this":[108,115],"work":[109,143],"under":[110],"CORDIC":[112],"algorithm.":[113],"Also,":[114],"defines":[117],"single":[119],"objective":[120],"function":[121],"relates":[123],"multi-constraints":[124],"like":[125],"Peak":[127],"Signal-to-Noise":[128],"Ratio":[129,135],"(PSNR)":[130],"well":[132],"Compression":[134],"(CR).":[136],"Finally,":[137],"performance":[139,152],"compared":[145],"over":[146],"other":[147],"conventional":[148],"models":[149],"regarding":[150],"certain":[151],"measures.":[153]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
