Fengyong Li , Qiankuan Wang , Xinpeng Zhang , Chuan Qin
{"title":"用于 JPEG 可逆数据隐藏的自适应三维直方图修改","authors":"Fengyong Li , Qiankuan Wang , Xinpeng Zhang , Chuan Qin","doi":"10.1016/j.sigpro.2024.109786","DOIUrl":null,"url":null,"abstract":"<div><div>JPEG reversible data hiding (RDH) is a data hiding technique that requires both accurate data extraction and perfect recovery of the original JPEG image. Existing JPEG RDH schemes often rely on the distortion model of DCT coefficient frequency itself, failing to fully utilize the correlation between adjacent coefficients, resulting in inferior visual quality and significant file size expansion for JPEG image containing hidden data. To address the problem, we design a new JPEG RDH scheme by introducing three-dimensional (3D) histogram modification mechanism. We firstly evaluate the costs of each DCT block and frequency band to build coefficient triplet grouping mechanism. Furthermore, we construct a series of three-dimensional histogram mappings to perform data embedding according to the grouped DCT coefficient triplets, and then optimize the embedding efficiency by adaptively integrating multi-dimensional histogram mapping for the given embedding capacity. Extensive experiments demonstrate that our scheme significantly outperforms the state-of-the-art JPEG RDH schemes and can achieve efficient balance between higher visual quality and smaller file size changes while keeping JPEG file format unchanged.</div></div>","PeriodicalId":49523,"journal":{"name":"Signal Processing","volume":"229 ","pages":"Article 109786"},"PeriodicalIF":3.4000,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Adaptive three-dimensional histogram modification for JPEG reversible data hiding\",\"authors\":\"Fengyong Li , Qiankuan Wang , Xinpeng Zhang , Chuan Qin\",\"doi\":\"10.1016/j.sigpro.2024.109786\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>JPEG reversible data hiding (RDH) is a data hiding technique that requires both accurate data extraction and perfect recovery of the original JPEG image. Existing JPEG RDH schemes often rely on the distortion model of DCT coefficient frequency itself, failing to fully utilize the correlation between adjacent coefficients, resulting in inferior visual quality and significant file size expansion for JPEG image containing hidden data. To address the problem, we design a new JPEG RDH scheme by introducing three-dimensional (3D) histogram modification mechanism. We firstly evaluate the costs of each DCT block and frequency band to build coefficient triplet grouping mechanism. Furthermore, we construct a series of three-dimensional histogram mappings to perform data embedding according to the grouped DCT coefficient triplets, and then optimize the embedding efficiency by adaptively integrating multi-dimensional histogram mapping for the given embedding capacity. Extensive experiments demonstrate that our scheme significantly outperforms the state-of-the-art JPEG RDH schemes and can achieve efficient balance between higher visual quality and smaller file size changes while keeping JPEG file format unchanged.</div></div>\",\"PeriodicalId\":49523,\"journal\":{\"name\":\"Signal Processing\",\"volume\":\"229 \",\"pages\":\"Article 109786\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2024-11-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0165168424004067\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0165168424004067","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
Adaptive three-dimensional histogram modification for JPEG reversible data hiding
JPEG reversible data hiding (RDH) is a data hiding technique that requires both accurate data extraction and perfect recovery of the original JPEG image. Existing JPEG RDH schemes often rely on the distortion model of DCT coefficient frequency itself, failing to fully utilize the correlation between adjacent coefficients, resulting in inferior visual quality and significant file size expansion for JPEG image containing hidden data. To address the problem, we design a new JPEG RDH scheme by introducing three-dimensional (3D) histogram modification mechanism. We firstly evaluate the costs of each DCT block and frequency band to build coefficient triplet grouping mechanism. Furthermore, we construct a series of three-dimensional histogram mappings to perform data embedding according to the grouped DCT coefficient triplets, and then optimize the embedding efficiency by adaptively integrating multi-dimensional histogram mapping for the given embedding capacity. Extensive experiments demonstrate that our scheme significantly outperforms the state-of-the-art JPEG RDH schemes and can achieve efficient balance between higher visual quality and smaller file size changes while keeping JPEG file format unchanged.
期刊介绍:
Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing.
Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.