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A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting
In this paper, we propose a novel joint data-hiding and compression scheme for digital images using side match vector quantization (SMVQ) and image inpainting. The two functions of data hiding and image compression can be integrated into one single module seamlessly. On the sender side, except for t...
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Published in: | IEEE transactions on image processing 2014-03, Vol.23 (3), p.969-978 |
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container_end_page | 978 |
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container_title | IEEE transactions on image processing |
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creator | Qin, Chuan Chang, Chin-Chen Chiu, Yi-Ping |
description | In this paper, we propose a novel joint data-hiding and compression scheme for digital images using side match vector quantization (SMVQ) and image inpainting. The two functions of data hiding and image compression can be integrated into one single module seamlessly. On the sender side, except for the blocks in the leftmost and topmost of the image, each of the other residual blocks in raster-scanning order can be embedded with secret data and compressed simultaneously by SMVQ or image inpainting adaptively according to the current embedding bit. Vector quantization is also utilized for some complex blocks to control the visual distortion and error diffusion caused by the progressive compression. After segmenting the image compressed codes into a series of sections by the indicator bits, the receiver can achieve the extraction of secret bits and image decompression successfully according to the index values in the segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme. |
doi_str_mv | 10.1109/TIP.2013.2260760 |
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The two functions of data hiding and image compression can be integrated into one single module seamlessly. On the sender side, except for the blocks in the leftmost and topmost of the image, each of the other residual blocks in raster-scanning order can be embedded with secret data and compressed simultaneously by SMVQ or image inpainting adaptively according to the current embedding bit. Vector quantization is also utilized for some complex blocks to control the visual distortion and error diffusion caused by the progressive compression. After segmenting the image compressed codes into a series of sections by the indicator bits, the receiver can achieve the extraction of secret bits and image decompression successfully according to the index values in the segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme.</description><identifier>ISSN: 1057-7149</identifier><identifier>EISSN: 1941-0042</identifier><identifier>DOI: 10.1109/TIP.2013.2260760</identifier><identifier>PMID: 23649221</identifier><identifier>CODEN: IIPRE4</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Algorithms ; Applied sciences ; Coding, codes ; Compressed ; Compressing ; Computer Security ; Cryptography ; Data Compression - methods ; Data hiding ; Diffusion barriers ; Digital images ; Distortion ; Erbium ; Exact sciences and technology ; Image coding ; Image compression ; image inpainting ; Image Interpretation, Computer-Assisted - methods ; Image processing ; Image segmentation ; Indexes ; Information, signal and communications theory ; Reproducibility of Results ; Sampling, quantization ; Sensitivity and Specificity ; side match vector quantization (SMVQ) ; Signal and communications theory ; Signal processing ; Signal Processing, Computer-Assisted ; Telecommunications and information theory ; Transaction processing ; Vector quantization</subject><ispartof>IEEE transactions on image processing, 2014-03, Vol.23 (3), p.969-978</ispartof><rights>2015 INIST-CNRS</rights><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Mar 2014</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c476t-f19f93709c0183bce943db5a703c20ccec377babba8648bbef324453a50e14bf3</citedby><cites>FETCH-LOGICAL-c476t-f19f93709c0183bce943db5a703c20ccec377babba8648bbef324453a50e14bf3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6510514$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27922,27923,54794</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=28496598$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/23649221$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Qin, Chuan</creatorcontrib><creatorcontrib>Chang, Chin-Chen</creatorcontrib><creatorcontrib>Chiu, Yi-Ping</creatorcontrib><title>A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting</title><title>IEEE transactions on image processing</title><addtitle>TIP</addtitle><addtitle>IEEE Trans Image Process</addtitle><description>In this paper, we propose a novel joint data-hiding and compression scheme for digital images using side match vector quantization (SMVQ) and image inpainting. The two functions of data hiding and image compression can be integrated into one single module seamlessly. On the sender side, except for the blocks in the leftmost and topmost of the image, each of the other residual blocks in raster-scanning order can be embedded with secret data and compressed simultaneously by SMVQ or image inpainting adaptively according to the current embedding bit. Vector quantization is also utilized for some complex blocks to control the visual distortion and error diffusion caused by the progressive compression. After segmenting the image compressed codes into a series of sections by the indicator bits, the receiver can achieve the extraction of secret bits and image decompression successfully according to the index values in the segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme.</description><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Coding, codes</subject><subject>Compressed</subject><subject>Compressing</subject><subject>Computer Security</subject><subject>Cryptography</subject><subject>Data Compression - methods</subject><subject>Data hiding</subject><subject>Diffusion barriers</subject><subject>Digital images</subject><subject>Distortion</subject><subject>Erbium</subject><subject>Exact sciences and technology</subject><subject>Image coding</subject><subject>Image compression</subject><subject>image inpainting</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image processing</subject><subject>Image segmentation</subject><subject>Indexes</subject><subject>Information, signal and communications theory</subject><subject>Reproducibility of Results</subject><subject>Sampling, quantization</subject><subject>Sensitivity and Specificity</subject><subject>side match vector quantization (SMVQ)</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Telecommunications and information theory</subject><subject>Transaction processing</subject><subject>Vector quantization</subject><issn>1057-7149</issn><issn>1941-0042</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><recordid>eNqNkV1LHDEUhkOpVN32vlAoASn0ZtZz8jWTS93aukWrRdvbIcmcsSPzsU52Bf-92e6q0KteJSHP-5Kch7H3CFNEsIfX88upAJRTIQzkBl6xPbQKMwAlXqc96DzLUdldth_jLQAqjeYN2xXSKCsE7rGrI_5juKeWfx-afsm_uKXLTpuq6W-46ys-G7rFSDE2Q8-vwh_qiB-7SBVfn89___wLzTt3Q3zeL1yqSMm3bKd2baR323XCfn09uZ6dZmcX3-azo7MsqNwssxptbWUONgAW0geySlZeuxxkEBACBZnn3nnvCqMK76mWQiktnQZC5Ws5YZ83vYtxuFtRXJZdEwO1retpWMUStQArVRrCf6CoTXpVqp-wg3_Q22E19ukja0pKmeapEgUbKoxDjCPV5WJsOjc-lAjl2k2Z3JRrN-XWTYp83BavfEfVc-BJRgI-bQEXg2vr0fWhiS9coazRtkjchw3XENHztdFJNyr5CCDPnBs</recordid><startdate>20140301</startdate><enddate>20140301</enddate><creator>Qin, Chuan</creator><creator>Chang, Chin-Chen</creator><creator>Chiu, Yi-Ping</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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The two functions of data hiding and image compression can be integrated into one single module seamlessly. On the sender side, except for the blocks in the leftmost and topmost of the image, each of the other residual blocks in raster-scanning order can be embedded with secret data and compressed simultaneously by SMVQ or image inpainting adaptively according to the current embedding bit. Vector quantization is also utilized for some complex blocks to control the visual distortion and error diffusion caused by the progressive compression. After segmenting the image compressed codes into a series of sections by the indicator bits, the receiver can achieve the extraction of secret bits and image decompression successfully according to the index values in the segmented sections. Experimental results demonstrate the effectiveness of the proposed scheme.</abstract><cop>New York, NY</cop><pub>IEEE</pub><pmid>23649221</pmid><doi>10.1109/TIP.2013.2260760</doi><tpages>10</tpages></addata></record> |
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subjects | Algorithms Applied sciences Coding, codes Compressed Compressing Computer Security Cryptography Data Compression - methods Data hiding Diffusion barriers Digital images Distortion Erbium Exact sciences and technology Image coding Image compression image inpainting Image Interpretation, Computer-Assisted - methods Image processing Image segmentation Indexes Information, signal and communications theory Reproducibility of Results Sampling, quantization Sensitivity and Specificity side match vector quantization (SMVQ) Signal and communications theory Signal processing Signal Processing, Computer-Assisted Telecommunications and information theory Transaction processing Vector quantization |
title | A Novel Joint Data-Hiding and Compression Scheme Based on SMVQ and Image Inpainting |
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