Reversible Data Hiding in JPEG Images Using Quantized DC

Reversible data hiding in JPEG images has become an important topic due to the prevalence and overwhelming support of the JPEG image format these days. Much of the existing work focuses on embedding using AC (quantized alternating current coefficients) to maximize the embedding capacity while minimi...

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Published inEntropy (Basel, Switzerland) Vol. 21; no. 9; p. 835
Main Authors Kim, Suah, Huang, Fangjun, Kim, Hyoung Joong
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 26.08.2019
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Abstract Reversible data hiding in JPEG images has become an important topic due to the prevalence and overwhelming support of the JPEG image format these days. Much of the existing work focuses on embedding using AC (quantized alternating current coefficients) to maximize the embedding capacity while minimizing the distortion and the file size increase. Traditionally, DC (quantized direct current coefficients) are not used for embedding, due to the assumption that the embedding in DCs cause more distortion than embedding in ACs. However, for data analytic which extracts fine details as a feature, distortion in ACs is not acceptable, because they represent the fine details of the image. In this paper, we propose a novel reversible data hiding method which efficiently embeds in the DC. The propose method uses a novel DC prediction method to decrease the entropy of the prediction error histogram. The embedded image has higher PSNR, embedding capacity, and smaller file size increase. Furthermore, proposed method preserves all the fine details of the image.
AbstractList Reversible data hiding in JPEG images has become an important topic due to the prevalence and overwhelming support of the JPEG image format these days. Much of the existing work focuses on embedding using AC (quantized alternating current coefficients) to maximize the embedding capacity while minimizing the distortion and the file size increase. Traditionally, DC (quantized direct current coefficients) are not used for embedding, due to the assumption that the embedding in DCs cause more distortion than embedding in ACs. However, for data analytic which extracts fine details as a feature, distortion in ACs is not acceptable, because they represent the fine details of the image. In this paper, we propose a novel reversible data hiding method which efficiently embeds in the DC. The propose method uses a novel DC prediction method to decrease the entropy of the prediction error histogram. The embedded image has higher PSNR, embedding capacity, and smaller file size increase. Furthermore, proposed method preserves all the fine details of the image.
Author Kim, Hyoung Joong
Kim, Suah
Huang, Fangjun
AuthorAffiliation 2 School of Data and Computer Science, Sun Yat-sen University, Guangzhou 510006, China
1 School of Information Security, Korea University, Seoul 02821, Korea
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Snippet Reversible data hiding in JPEG images has become an important topic due to the prevalence and overwhelming support of the JPEG image format these days. Much of...
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SubjectTerms Alternating current
Data analysis
DC coefficients
DCT coefficients
Direct current
Distortion
Embedding
Entropy
Feature extraction
Histograms
Image compression
JPEG
JPEG encoders-decoders
reversible data hiding
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Title Reversible Data Hiding in JPEG Images Using Quantized DC
URI https://www.proquest.com/docview/2548389274
https://pubmed.ncbi.nlm.nih.gov/PMC7515364
https://doaj.org/article/5ee623b3b32441ce88974c04b434b719
Volume 21
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