{"id":"https://openalex.org/W7123338725","doi":"https://doi.org/10.1109/lsp.2026.3652378","title":"A Dual-Reward Guided 2D Mapping Generation Network for JPEG Reversible Data Hiding","display_name":"A Dual-Reward Guided 2D Mapping Generation Network for JPEG Reversible Data Hiding","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7123338725","doi":"https://doi.org/10.1109/lsp.2026.3652378"},"language":null,"primary_location":{"id":"doi:10.1109/lsp.2026.3652378","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3652378","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","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":null,"display_name":"Rui Yan","orcid":"https://orcid.org/0009-0001-4467-7510"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yan","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0001-4467-7510","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122864064","display_name":"Yao Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yao Zhao","raw_affiliation_strings":["Institute of Information Science, Beijing Jiaotong University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-8581-9554","affiliations":[{"raw_affiliation_string":"Institute of Information Science, Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5122874828","display_name":"Shaowei Weng","orcid":null},"institutions":[{"id":"https://openalex.org/I83791580","display_name":"Fujian University of Technology","ror":"https://ror.org/03c8fdb16","country_code":"CN","type":"education","lineage":["https://openalex.org/I83791580"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shaowei Weng","raw_affiliation_strings":["Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-1037-7699","affiliations":[{"raw_affiliation_string":"Fujian Provincial Key Laboratory of Big Data Mining and Applications, Fujian University of Technology, Fuzhou, China","institution_ids":["https://openalex.org/I83791580"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067543068","display_name":"Lifang Yu","orcid":"https://orcid.org/0000-0002-0508-7526"},"institutions":[{"id":"https://openalex.org/I4210135483","display_name":"Beijing Institute of Graphic Communication","ror":"https://ror.org/03yg3v757","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210135483"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lifang Yu","raw_affiliation_strings":["Department of Information Engineering, Beijing Institute of Graphic Communication, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0508-7526","affiliations":[{"raw_affiliation_string":"Department of Information Engineering, Beijing Institute of Graphic Communication, Beijing, China","institution_ids":["https://openalex.org/I4210135483"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":17.6924,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.96806029,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"33","issue":null,"first_page":"526","last_page":"530"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.8381999731063843,"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/T10388","display_name":"Advanced Steganography and Watermarking Techniques","score":0.8381999731063843,"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/T12357","display_name":"Digital Media Forensic Detection","score":0.14059999585151672,"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/T11017","display_name":"Chaos-based Image/Signal Encryption","score":0.002199999988079071,"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/payload","display_name":"Payload (computing)","score":0.8586000204086304},{"id":"https://openalex.org/keywords/information-hiding","display_name":"Information hiding","score":0.67330002784729},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.5684999823570251},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.4767000079154968},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4715999960899353},{"id":"https://openalex.org/keywords/jpeg","display_name":"JPEG","score":0.41100001335144043},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.38659998774528503}],"concepts":[{"id":"https://openalex.org/C134066672","wikidata":"https://www.wikidata.org/wiki/Q1424639","display_name":"Payload (computing)","level":3,"score":0.8586000204086304},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7181000113487244},{"id":"https://openalex.org/C3073032","wikidata":"https://www.wikidata.org/wiki/Q15912075","display_name":"Information hiding","level":3,"score":0.67330002784729},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.5684999823570251},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.4767000079154968},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4715999960899353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46709999442100525},{"id":"https://openalex.org/C198751489","wikidata":"https://www.wikidata.org/wiki/Q2195","display_name":"JPEG","level":3,"score":0.41100001335144043},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.38659998774528503},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3619000017642975},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33959999680519104},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.3337000012397766},{"id":"https://openalex.org/C108801101","wikidata":"https://www.wikidata.org/wiki/Q15032","display_name":"Steganography","level":3,"score":0.3102000057697296},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.298799991607666},{"id":"https://openalex.org/C28855332","wikidata":"https://www.wikidata.org/wiki/Q198099","display_name":"Quantization (signal processing)","level":2,"score":0.29249998927116394},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.2896000146865845},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2644999921321869},{"id":"https://openalex.org/C77618280","wikidata":"https://www.wikidata.org/wiki/Q1155772","display_name":"Scheme (mathematics)","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.257999986410141}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lsp.2026.3652378","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2026.3652378","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Signal Processing Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":34,"referenced_works":["https://openalex.org/W22271197","https://openalex.org/W1974641035","https://openalex.org/W2041860486","https://openalex.org/W2056340285","https://openalex.org/W2066178754","https://openalex.org/W2078607543","https://openalex.org/W2085640111","https://openalex.org/W2106950225","https://openalex.org/W2117314358","https://openalex.org/W2121393355","https://openalex.org/W2135459805","https://openalex.org/W2137288380","https://openalex.org/W2140226570","https://openalex.org/W2144088652","https://openalex.org/W2152185406","https://openalex.org/W2162434844","https://openalex.org/W2509384312","https://openalex.org/W2594085527","https://openalex.org/W2753596415","https://openalex.org/W2790708594","https://openalex.org/W2793917896","https://openalex.org/W2995564652","https://openalex.org/W2998870215","https://openalex.org/W3029954326","https://openalex.org/W3091141192","https://openalex.org/W3161577134","https://openalex.org/W3195437128","https://openalex.org/W4210449676","https://openalex.org/W4214751967","https://openalex.org/W4281810205","https://openalex.org/W4293198382","https://openalex.org/W4318822639","https://openalex.org/W4401725215","https://openalex.org/W4410737507"],"related_works":[],"abstract_inverted_index":{"Recently,":[0],"researchers":[1],"have":[2],"shifted":[3],"focus":[4],"to":[5,23,55,80,128,178,221],"reversible":[6],"data":[7,148,160],"hiding":[8],"(RDH)":[9],"schemes":[10,226],"for":[11,21,31,146,159,227],"JPEG":[12,228],"images.":[13,229],"The":[14],"reinforcement":[15],"learning":[16],"(RL)":[17],"is":[18,144,176,219],"a":[19,67,83,162],"solution":[20],"RDH":[22,225],"automatically":[24],"acquire":[25],"the":[26,43,52,56,111,129,132,135,153,167,173,180,191,199,208,212,216],"optimal":[27],"two-dimensional":[28],"(2D)":[29],"mapping":[30,58,87],"2D":[32,57,86,99,142],"histograms":[33],"of":[34,172,182],"non-zero":[35],"quantized":[36],"alternating":[37],"current":[38],"coefficients.":[39],"However,":[40],"merely":[41,107],"utilizing":[42,108],"payload-distortion":[44],"reward":[45,70],"mechanism":[46,71],"(PDRM)":[47],"in":[48],"RL":[49,79],"cannot":[50],"inject":[51],"payload":[53,68,93,118],"guidance":[54],"generation":[59,88],"process.":[60],"To":[61,150],"tackle":[62],"this":[63],"issue,":[64],"we":[65],"propose":[66],"supplementary":[69],"(PSRM)":[72],"and":[73,76,110,116,124,169,189,202,211],"incorporate":[74],"PDRM":[75,109,123],"PSRM":[77],"into":[78],"construct":[81],"DR-2DNet,":[82],"dual-reward":[84],"guided":[85],"network":[89],"with":[90,102,113,134,156],"considering":[91],"additional":[92],"guidance.":[94],"DR-2DNet":[95],"generates":[96],"two":[97,140],"candidate":[98],"mappings,":[100],"one":[101,133],"low":[103,114,157],"distortion":[104,115,137,188],"generated":[105],"by":[106,120],"other":[112],"high":[117],"obtained":[119],"jointly":[121],"using":[122],"PSRM.":[125],"Finally,":[126],"according":[127],"required":[130],"payload,":[131],"lower":[136],"selected":[138],"from":[139,207],"acquired":[141],"mappings":[143],"used":[145],"achieving":[147],"embedding.":[149],"priorly":[151],"select":[152],"frequency":[154,163,174,184],"bands":[155],"costs":[158],"embedding,":[161],"selection":[164],"strategy":[165],"combining":[166],"smoothness":[168],"embedding":[170],"performance":[171],"band":[175],"designed":[177],"evaluate":[179],"cost":[181],"each":[183],"band,":[185],"reducing":[186],"image":[187],"preserving":[190],"file":[192],"size.":[193],"Extensive":[194],"experiments":[195],"are":[196],"conducted":[197],"on":[198],"Kodak":[200],"dataset":[201],"100":[203],"images":[204],"randomly":[205],"chosen":[206],"BOSSBase":[209],"dataset,":[210],"results":[213],"demonstrate":[214],"that":[215],"proposed":[217],"method":[218],"superior":[220],"several":[222],"related":[223],"state-of-the-art":[224]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-01-14T00:00:00"}
