A greedy steganographic SMVQ approach of greedy-USBIRDS using secret bits for image-block repairing based on differences

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Title:	A greedy steganographic SMVQ approach of greedy-USBIRDS using secret bits for image-block repairing based on differences
Authors:	王尉任;Wang, Wei-Jen;Huang, Cheng-Ta;Tsuei, Shiau-Rung;WANG, Shiuh-Jeng
Contributors:	資訊電機學院資訊工程學系
Keywords:	Analysis;Communication;Compressing;Computer Communication Networks;Computer Science;Cryptography;Data Structures and Information Theory;Handles;Image processing systems;Image quality;Internet;Inventors;Maintenance;Methods;Multimedia;Multimedia computer applications;Multimedia Information Systems;Optimization;Repairing;Signal to noise ratio;Special Purpose and Application-Based Systems;Steganography;Studies
Date:	2016-11-01
Issue Date:	2026-04-23 13:04:10 (UTC+8)
Publisher:	Springer Netherlands;New York: Springer US
Abstract:	摘要： Steganography conceals the secret data into cover media to avoid detection, such that no one suspects the existence of the embedded secret data. The existing VQ-based and SMVQ-based steganographic methods can only provide the same level of visual quality of what the VQ/SMVQ compression method can offer. In this study, we present the idea of using secret bits to repair SMVQ-compressed images. The idea can be viewed as the optimization problem of Using Secret Bits for Image-block Repairing based on Differences under SMVQ (USBIRDS). We propose a novel approach named Greedy-USBIRDS to find a near optimal solution for the USBIRDS problem. The experimental results show that, the proposed method provides excellent stego-image quality and large embedding capacity, in particular for complex cover images such as Baboon. While compared with Chen and Lin’s steganographic method, which is the known best method based on VQ/SMVQ, the proposed method achieves about 53 % more dB of PSNR of the stego-image quality and about 4.2 % more bits of the embedding capacity on average. All the experimental results indicate that, this study makes significant contributions to the area of VQ-based and SMVQ-based steganography, especially for its excellent stego-image quality and its ability to handle complex cover images very well. 其他題名： Multimed Tools Appl 出版者： New York: Springer US 出版日期： 2016-11-01 出處： Multimedia tools and applications, 2016-11, Vol.75 (22), p.14895-14916 資源來源： ProQuest ABI/INFORM Global 版權： Springer Science+Business Media New York 2015 版權： Multimedia Tools and Applications is a copyright of Springer, 2016. 識別號： ISSN: 1380-7501 識別號： EISSN: 1573-7721 識別號： DOI: 10.1007/s11042-015-2761-8
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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