High Capacity Data Hiding in JPEG‐Compressed Images

Tseng, Hsien-Wen; Chang, Chin‐Chen

doi:10.15388/informatica.2004.050

Cited by 50 publications

(25 citation statements)

References 11 publications

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“…Peak signal-to-noise ratio (PSNR) is used to estimate the visual quality of the stego-images compared to the original images. The definitions of mean square error (MSE) and PSNR are shown in Equations (15) and (16), respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Therefore, data hiding methods in the compressed domain have received more attention. Various data hiding methods in different compression techniques have been proposed, such as vector quantization (VQ) [13], side match vector quantization (SMVQ) [14], joint photographic experts group (JPEG) [15], block truncation coding (BTC), and absolute moment block truncation coding (AMBTC). The BTC compression method divides an image into non-overlapping blocks and stores two quantization values and a bitmap of each block as one compressed block code [16].…”

Section: Introductionmentioning

confidence: 99%

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A Hybrid Data Hiding Method for Strict AMBTC Format Images with High-Fidelity

2019

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With the rapid development of smartphones, cloud storage, and wireless communications, protecting the security of compressed images through data transmission on the Internet has become a critical contemporary issue. A series of data hiding methods for AMBTC compressed images has been proposed to solve this problem. However, most of these methods either change the file size of the final compressed code or exchange the order of two quantization values in some blocks. To reverse this situation, this paper proposes a data hiding method for strict AMBTC format images using a hybrid strategy: replacement, matrix encoding, and symmetric quantization value embedding for three block types i.e., smooth blocks, less complex blocks and highly complex blocks. According to the hybrid strategy, an efficient data hiding order is designed to achieve higher-fidelity. Experimental results show that our proposed method provides an excellent balance between image quality and hiding capacity and has no error blocks in the final stego-compressed code.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Hybrid Data Hiding Method for Strict AMBTC Format Images with High-Fidelity

2019

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“…Many papers have been published that are dealing with data hiding in JPEG images [7–9], but only a few of them are concerned about reversibility. In the paper by Fridrich et al .…”

Section: Introductionmentioning

confidence: 99%

Reversible data hiding in JPEG images utilising zero quantised coefficients

Nikolaidis

2015

IET Image Processing

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A novel technique for data hiding in JPEG images is proposed. The technique relies on modification of zero quantised coefficients in each image block, in contrast to most previously proposed methods which also affect nonzero coefficients and/or the quantisation tables. Both embedding and extraction are performed on a per-block basis, without the need to preprocess the whole image. The proposed technique provides significantly lower distortion for similar embedding capacity, compared with recent state-of-the-art techniques.

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“…Data hiding can be divided into two basic categories based on reversibility. The first is irreversible data hiding [1][2][3][4]. The advantage of irreversible data hiding is that a large amount of secret information can be embedded and transmitted in the popular channel.…”

Section: Introductionmentioning

confidence: 99%

“…Many imagecompressed data hiding schemes have been noted in the literature because the sizes of the compressed images will be much smaller than those of the original images before and after data hiding. Various compression techniques, i.e., JPEG [1,2], block truncation coding (BTC) [17], vector quantization (VQ) and side-match vector quantization (SMVQ) [5][6][7][8][9][10][11][12] have been utilized for data hiding to obtain both a low compression rate and high embedding capacity.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Lossless Data Hiding Scheme for SMVQ-Compressed Images using SOC Coding

Nguyen¹,

Chang²,

Lin³

2014

SmartCR

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Lossless data hiding recovers original images precisely after secret data are extracted. Therefore, it has received considerable attention among researchers. This paper offers an adaptive lossless data hiding scheme that is based on the search-order coding (SOC) algorithm for side match vector quantization (SMVQ) compressed images. By combining SOC coding with the SMVQ algorithm, compression performance is further improved while a large amount of free space is generated to hide secret data during the data embedding phase. In the extracting phase, simple steps are used to extract that embedded secret data. The same index table can be reconstructed on the receiver side, which ensures that this proposed scheme can restore the original cover image exactly. Experimental results have demonstrated that the proposed scheme yields a higher embedding rate and a lower compression rate than other related VQ and SMVQ based data hiding schemes.

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High Capacity Data Hiding in JPEG‐Compressed Images

Cited by 50 publications

References 11 publications

A Hybrid Data Hiding Method for Strict AMBTC Format Images with High-Fidelity

A Hybrid Data Hiding Method for Strict AMBTC Format Images with High-Fidelity

Reversible data hiding in JPEG images utilising zero quantised coefficients

Adaptive Lossless Data Hiding Scheme for SMVQ-Compressed Images using SOC Coding

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