W
Wien Hong
Researcher at Sun Yat-sen University
Publications - 81
Citations - 2900
Wien Hong is an academic researcher from Sun Yat-sen University. The author has contributed to research in topics: Information hiding & Pixel. The author has an hindex of 23, co-authored 77 publications receiving 2441 citations. Previous affiliations of Wien Hong include Yu Da University & National Taichung University of Science and Technology.
Papers
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Journal ArticleDOI
An Improved Reversible Data Hiding in Encrypted Images Using Side Match
TL;DR: This letter adopts a better scheme for measuring the smoothness of blocks, and uses the side-match scheme to further decrease the error rate of extracted-bits in an improved version of Zhang's reversible data hiding method in encrypted images.
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Reversible data hiding for high quality images using modification of prediction errors
TL;DR: Experimental results indicate that MPE, which innovatively exploits the modification of prediction errors, outperforms the prior works not only in terms of larger payload, but also in Terms of stego image quality.
Journal ArticleDOI
A Novel Data Embedding Method Using Adaptive Pixel Pair Matching
Wien Hong,Tung-Shou Chen +1 more
TL;DR: Experimental results reveal that the proposed method offers lower distortion than DE by providing more compact neighborhood sets and allowing embedded digits in any notational system and is secure under the detection of some well-known steganalysis techniques.
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Encrypted image-based reversible data hiding with public key cryptography from difference expansion
TL;DR: The core of the proposed scheme is to pre-process an image with the property of difference expansion before encrypting, which provides good payload and image quality and shows the effectiveness of this scheme.
Journal ArticleDOI
Adaptive reversible data hiding method based on error energy control and histogram shifting
TL;DR: An adaptive method to increase the number of embeddable spaces by referencing a dual binary tree is proposed and significantly improves the image quality and payload of Tai et al.'s works, especially at low embedding level.