{"id":"https://openalex.org/W1514231092","doi":"https://doi.org/10.1109/icip.2003.1247281","title":"Two error resilient coding schemes for wavelet-based image transmission based on data embedding and genetic algorithms","display_name":"Two error resilient coding schemes for wavelet-based image transmission based on data embedding and genetic algorithms","publication_year":2004,"publication_date":"2004-06-03","ids":{"openalex":"https://openalex.org/W1514231092","doi":"https://doi.org/10.1109/icip.2003.1247281","mag":"1514231092"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2003.1247281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2003.1247281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429)","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/A5106664802","display_name":"Li\u2010Wei Kang","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Li-Wei Kang","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan , Republic of China","Dept. of Comput. Sci. & Information Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan , Republic of China","institution_ids":["https://openalex.org/I148099254"]},{"raw_affiliation_string":"Dept. of Comput. Sci. & Information Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan#TAB#","institution_ids":["https://openalex.org/I148099254"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109006511","display_name":"Jin-Jang Leou","orcid":null},"institutions":[{"id":"https://openalex.org/I148099254","display_name":"National Chung Cheng University","ror":"https://ror.org/0028v3876","country_code":"TW","type":"education","lineage":["https://openalex.org/I148099254"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Jin-Jang Leou","raw_affiliation_strings":["Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan , Republic of China","Dept. of Comput. Sci. & Information Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Information Engineering, National Chung Cheng University, Chiayi, Taiwan , Republic of China","institution_ids":["https://openalex.org/I148099254"]},{"raw_affiliation_string":"Dept. of Comput. Sci. & Information Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan#TAB#","institution_ids":["https://openalex.org/I148099254"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I148099254"],"apc_list":null,"apc_paid":null,"fwci":1.4269,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79356401,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"2","issue":null,"first_page":"III","last_page":"461"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10901","display_name":"Advanced Data Compression Techniques","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/T10901","display_name":"Advanced Data Compression Techniques","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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9993000030517578,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9965999722480774,"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/code-word","display_name":"Code word","score":0.7210182547569275},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5927319526672363},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5810627937316895},{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.5724422335624695},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.534876823425293},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.45236465334892273},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.43025699257850647},{"id":"https://openalex.org/keywords/data-compression","display_name":"Data compression","score":0.3780890107154846},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3671987056732178},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.347138911485672},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.19252613186836243}],"concepts":[{"id":"https://openalex.org/C153207627","wikidata":"https://www.wikidata.org/wiki/Q863873","display_name":"Code word","level":3,"score":0.7210182547569275},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5927319526672363},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5810627937316895},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.5724422335624695},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.534876823425293},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.45236465334892273},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.43025699257850647},{"id":"https://openalex.org/C78548338","wikidata":"https://www.wikidata.org/wiki/Q2493","display_name":"Data compression","level":2,"score":0.3780890107154846},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3671987056732178},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.347138911485672},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.19252613186836243}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2003.1247281","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2003.1247281","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429)","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":37,"referenced_works":["https://openalex.org/W621349779","https://openalex.org/W1481550144","https://openalex.org/W1771954171","https://openalex.org/W1846552414","https://openalex.org/W1925881876","https://openalex.org/W1964200283","https://openalex.org/W2039898912","https://openalex.org/W2072483035","https://openalex.org/W2096962810","https://openalex.org/W2099563019","https://openalex.org/W2100224231","https://openalex.org/W2103064448","https://openalex.org/W2106069707","https://openalex.org/W2106667790","https://openalex.org/W2107635865","https://openalex.org/W2113472437","https://openalex.org/W2115746918","https://openalex.org/W2117458116","https://openalex.org/W2118217749","https://openalex.org/W2120519728","https://openalex.org/W2123455204","https://openalex.org/W2129782342","https://openalex.org/W2136454656","https://openalex.org/W2139514636","https://openalex.org/W2142183404","https://openalex.org/W2148046492","https://openalex.org/W2149815901","https://openalex.org/W2152981638","https://openalex.org/W2157971981","https://openalex.org/W2161199351","https://openalex.org/W2162230247","https://openalex.org/W2162287270","https://openalex.org/W2165320487","https://openalex.org/W2166168490","https://openalex.org/W2534745951","https://openalex.org/W6637911835","https://openalex.org/W6683759950"],"related_works":["https://openalex.org/W88624181","https://openalex.org/W4322741006","https://openalex.org/W2081900870","https://openalex.org/W2910428196","https://openalex.org/W2120205576","https://openalex.org/W2134324324","https://openalex.org/W2369939250","https://openalex.org/W2183306018","https://openalex.org/W2549990292","https://openalex.org/W2743579231"],"abstract_inverted_index":{"For":[0,75,93,133,153],"an":[1,65,78],"entropy-coded":[2],"wavelet-based":[3,47,202],"image,":[4,9],"such":[5],"as":[6,63],"a":[7,10,14,31,106,122,141,212],"JPEG-2000":[8,203],"transmission":[11,49],"error":[12,42,79,124,214],"in":[13,30,175],"codeword":[15,22],"will":[16],"not":[17],"only":[18],"affects":[19],"the":[20,35,96,101,112,117,129,136,149,156,171,178,181,190,206],"underlying":[21],"but":[23],"also":[24],"may":[25],"affect":[26],"subsequent":[27],"codewords,":[28],"resulting":[29],"great":[32],"degradation":[33],"of":[34,159,180,189,216],"received":[36],"image.":[37],"In":[38,60],"this":[39,61,176],"study,":[40,62,177],"two":[41,182],"resilient":[43,80],"coding":[44,81],"schemes":[45,184,198],"for":[46,105,140,194],"image":[48,66],"based":[50,83],"on":[51,84,170],"data":[52,85,104,139],"embedding":[53,86],"and":[54,87],"genetic":[55],"algorithms":[56],"(GAs)":[57],"are":[58,145,164,185],"proposed.":[59],"JPEG-2000,":[64],"is":[67,91],"decomposed":[68],"into":[69],"6":[70],"wavelet":[71,157],"levels":[72,154],"(levels":[73],"0-5).":[74],"level":[76,94,134],"0,":[77],"scheme":[82,99,120,126],"side-match":[88],"vector":[89],"quantization":[90],"employed.":[92],"1,":[95],"proposed":[97,118,183,197],"basic":[98],"uses":[100,121],"embedded":[102,137],"important":[103,138],"corrupted":[107,113,130,142,150,161,208],"code":[108,114,131,143,151,162],"block":[109,144,163],"to":[110,127,147,211],"conceal":[111,128,148],"block,":[115],"whereas":[116],"enhanced":[119],"GA-based":[123],"concealment":[125],"block.":[132,152],"2,":[135],"used":[146],"3-5,":[155],"coefficients":[158],"each":[160],"simply":[165],"replaced":[166],"by":[167],"zeros.":[168],"Based":[169],"simulation":[172],"results":[173],"obtained":[174],"performances":[179],"better":[186],"than":[187],"that":[188],"three":[191],"existing":[192],"approaches":[193],"comparison.":[195],"The":[196],"can":[199],"recover":[200],"high-quality":[201],"images":[204,209],"from":[205],"corresponding":[207],"up":[210],"bit":[213],"rate":[215],"0.5%.":[217]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}