The Experts below are selected from a list of 30762 Experts worldwide ranked by ideXlab platform
Chin-chen Chang - One of the best experts on this subject based on the ideXlab platform.
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reversible steganographic scheme for ambtc Compressed Image based on 7 4 hamming code
Symmetry, 2019Co-Authors: Chin-chen ChangAbstract:In recent years, compression steganography technology has attracted the attention of many scholars. Among all Image compression method, absolute moment block truncation coding (AMBTC) is a simple and effective compression method. Most AMBTC-based reversible data hiding (RDH) schemes do not guarantee that the stego AMBTC compression codes can be translated by the conventional AMBTC decoder. In other words, they do not belong to Type I AMBTC-based RDH scheme and easily attract malicious users’ attention. To solve this problem and enhance the hiding capacity, we used (7,4) hamming code to design a Type I AMBTC-based RDH scheme in this paper. To provide the reversibility feature, we designed a prediction method and judgement mechanism to successfully select the embeddable blocks during the data embedding phase and data extraction and recovery phase. In comparing our approach with other BTC-based schemes, it is confirmed that our hiding capacity is increased while maintaining the limited size of the compression codes and acceptable Image quality of the stego AMBTC-Compressed Images.
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bi stretch reversible data hiding algorithm for absolute moment block truncation coding Compressed Images
Multimedia Tools and Applications, 2016Co-Authors: K Bharanitharan, Chin-chen Chang, Qian MaoAbstract:Steganography is one of the most important approaches for secure transmission by concealing secret data into a host Image imperceptibly. To achieve a good tradeoff between the hiding capacity and Image quality, more work needs to be further researched. In this paper, to obtain satisfactory results, a Bi-Stretch Hiding (BSH) algorithm for absolute moment block truncation coding (AMBTC)-Compressed Image is proposed. In the scheme, the AMBTC-Compressed Image is divided into non-overlapped blocks first, after that, four feasible cases are employed to embed secret data, which takes advantage of the characteristics of the coefficients of the AMBTC-Compressed Image and lead tiny distortion of the AMBTC-Compressed Image. The experimental results demonstrate that the proposed BSH scheme outperforms the other state-of-the-art compression data hiding methods.
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reversible index domain information hiding scheme based on side match vector quantization
Journal of Systems and Software, 2006Co-Authors: Chin-chen Chang, Tzuchuen LuAbstract:Information hiding has become an interesting topic that receives more and more attention. Recently, many hiding techniques were proposed to directly conceal secret information on an Image. However, for convenience and efficiency, Images are usually stored and Compressed by lossy or lossless compression mechanisms in indices format. The hidden information might be erased or cancelled when the stego Image is lossy Compressed. Hence, this paper proposes an information hiding scheme based on side-match vector quantization (SMVQ), which conceals the secret information on the indices of the SMVQ Compressed Images. The proposed scheme not only can embed information in the indices of the Compressed Image with low Image distortion, but also can recover the original indices to reconstruct the SMVQ Compressed Image. As the experimental results indicated, the proposed scheme indeed outperforms other schemes in terms of Image quality, hiding capacity, and compression rate.
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a novel digital Image watermarking scheme based on the vector quantization technique
Computers & Security, 2005Co-Authors: Hsienchu Wu, Chin-chen ChangAbstract:In this paper, a novel VQ-based digital Image watermarking scheme is proposed. During the encoding process of the VQ compression technique, the proposed scheme embeds a representative digital watermark in the protected Image so that the watermark can be retrieved from the Image to effectively prove which party is in legal possession of the copyright in case an ownership dispute arises. In our method, the codewords in the VQ codebook are classified into different groups according to different characteristics and then each binary watermark bit is embedded into the selected VQ encoded block. The main feature of the proposed scheme is that the watermark exists both in the VQ Compressed Image and in the reconstructed Image after VQ decoding. Because the watermark is hidden inside the Compressed Image, which is much smaller in size, much transmission time and storage space can be saved when the Compressed data, instead of the original form, are transmitted over the Internet. Furthermore, the reconstructed Image has robustness against aggressive Image processing. The embedded watermark can even survive JPEG lossy compression.
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Retrieving digital Images from a JPEG Compressed Image database
Image and Vision Computing, 2004Co-Authors: Chin-chen Chang, Jun-chou ChuangAbstract:Abstract In this paper, we propose a new method of feature extraction in order to improve the efficiency of retrieving Joint Photographic Experts Group (JPEG) Compressed Images. Our feature extraction can be done directly to JPEG Compressed Images. We extract two features, DC feature and AC feature, from a JPEG Compressed Image. Then we measure the distances between the query Image and the Images in a database in terms of these two features. Our Image retrieval system will give each retrieved Image a rank to define its similarity to the query Image. Furthermore, instead of fully decompressing JPEG Images, our system only needs to do partial entropy decoding. Therefore, our proposed scheme can accelerate the work of retrieving Images. According to our experimental results, our system is not only highly efficient but is also capable of performing satisfactorily.
Sam Kwong - One of the best experts on this subject based on the ideXlab platform.
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Compressed Image Quality Assessment Based on Saak Features.
arXiv: Image and Video Processing, 2019Co-Authors: Xinfeng Zhang, Sam Kwong, C.-c. Jay KuoAbstract:Compressed Image quality assessment plays an important role in Image services, especially in Image compression applications, which can be utilized as a guidance to optimize Image processing algorithms. In this paper, we propose an objective Image quality assessment algorithm to measure the quality of Compressed Images. The proposed method utilizes a data-driven transform, Saak (Subspace approximation with augmented kernels), to decompose Images into hierarchical structural feature space. We measure the distortions of Saak features and accumulate these distortions according to the feature importance to human visual system. Compared with the state-of-the-art Image quality assessment methods on widely utilized datasets, the proposed method correlates better with the subjective results. In addition, the proposed methods achieves more robust results on different datasets.
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ICIP - Compressed Image Quality Assessment Based on Saak Features
2019 IEEE International Conference on Image Processing (ICIP), 2019Co-Authors: Xinfeng Zhang, Sam Kwong, C.-c. Jay KuoAbstract:Compressed Image quality assessment plays an important role in Image services, especially in Image compression applications, which can be utilized as a guidance to optimize Image processing algorithms. In this paper, we propose an objective Image quality assessment algorithm to measure the quality of Compressed Images. The proposed method utilizes a data-driven transform, Saak (Subspace approximation with augmented kernels), to decompose Images into hierarchical structural feature space. We measure the distortions of Saak features and accumulate these distortions according to the feature importance to human visual system. Compared with the state-of-the-art Image quality assessment methods on widely utilized datasets, the proposed method correlates better with the subjective results. In addition, the proposed methods achieves more robust results on different datasets.
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Compressed Image quality metric based on perceptually weighted distortion
IEEE Transactions on Image Processing, 2015Co-Authors: Sudeng Hu, Hanli Wang, Yun Zhang, Sam KwongAbstract:Objective quality assessment for Compressed Images is critical to various Image compression systems that are essential in Image delivery and storage. Although the mean squared error (MSE) is computationally simple, it may not be accurate to reflect the perceptual quality of Compressed Images, which is also affected dramatically by the characteristics of human visual system (HVS), such as masking effect. In this paper, an Image quality metric (IQM) is proposed based on perceptually weighted distortion in terms of the MSE. To capture the characteristics of HVS, a randomness map is proposed to measure the masking effect and a preprocessing scheme is proposed to simulate the processing that occurs in the initial part of HVS. Since the masking effect highly depends on the structural randomness, the prediction error from neighborhood with a statistical model is used to measure the significance of masking. Meanwhile, the imperceptible signal with high frequency could be removed by preprocessing with low-pass filters. The relation is investigated between the distortions before and after masking effect, and a masking modulation model is proposed to simulate the masking effect after preprocessing. The performance of the proposed IQM is validated on six Image databases with various compression distortions. The experimental results show that the proposed algorithm outperforms other benchmark IQMs.
Tzuchuen Lu - One of the best experts on this subject based on the ideXlab platform.
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reversible index domain information hiding scheme based on side match vector quantization
Journal of Systems and Software, 2006Co-Authors: Chin-chen Chang, Tzuchuen LuAbstract:Information hiding has become an interesting topic that receives more and more attention. Recently, many hiding techniques were proposed to directly conceal secret information on an Image. However, for convenience and efficiency, Images are usually stored and Compressed by lossy or lossless compression mechanisms in indices format. The hidden information might be erased or cancelled when the stego Image is lossy Compressed. Hence, this paper proposes an information hiding scheme based on side-match vector quantization (SMVQ), which conceals the secret information on the indices of the SMVQ Compressed Images. The proposed scheme not only can embed information in the indices of the Compressed Image with low Image distortion, but also can recover the original indices to reconstruct the SMVQ Compressed Image. As the experimental results indicated, the proposed scheme indeed outperforms other schemes in terms of Image quality, hiding capacity, and compression rate.
Jing-ming Guo - One of the best experts on this subject based on the ideXlab platform.
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Reversible Data Hiding Scheme with High Embedding Capacity Using Semi-Indicator-Free Strategy
Mathematical Problems in Engineering, 2013Co-Authors: Jiann-der Lee, Yaw-hwang Chiou, Jing-ming GuoAbstract:A novel reversible data-hiding scheme is proposed to embed secret data into a side-matched-vector-quantization- (SMVQ-) Compressed Image and achieve lossless reconstruction of a vector-quantization- (VQ-) Compressed Image. The rather random distributed histogram of a VQ-Compressed Image can be relocated to locations close to zero by SMVQ prediction. With this strategy, fewer bits can be utilized to encode SMVQ indices with very small values. Moreover, no indicator is required to encode these indices, which yields extrahiding space to hide secret data. Hence, high embedding capacity and low bit rate scenarios are deposited. More specifically, in terms of the embedding rate, the bit rate, and the embedding capacity, experimental results show that the performance of the proposed scheme is superior to those of the former data hiding schemes for VQ-based, VQ/SMVQ-based, and search-order-coding- (SOC-) based Compressed Images.
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SiPS - Reversible data hiding scheme with high embedding capacity using semi-indicator-free strategy
SiPS 2013 Proceedings, 2013Co-Authors: Jiann-der Lee, Yaw-hwang Chiou, Jing-ming GuoAbstract:This work presents a novel reversible data-hiding scheme which embeds secret data into a side matched Vector Quantization (SMVQ)-Compressed Image, and achieves lossless reconstruction of a Vector Quantization (VQ)-Compressed Image. The rather random distributed histogram of a VQ-Compressed Image can be re-located to locations close to zero by SMVQ prediction. Thus, fewer bits can be used to encode SMVQ indices with very small values, and no indicator is required to encode these indices, which yields extra hiding space to hide secret data. Consequently, high embedding capacity and low bit rate scenarios can be deposited. Experimental results demonstrate the effectiveness and reversibility of the proposed scheme. Moreover, in terms of the embedding rate, the bit rate, and the embedding capacity, experimental results show that the performance of the proposed scheme is better than those of the former data hiding schemes for VQ-based and VQ/SMVQ-based Compressed Images.
Hsienchu Wu - One of the best experts on this subject based on the ideXlab platform.
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a novel digital Image watermarking scheme based on the vector quantization technique
Computers & Security, 2005Co-Authors: Hsienchu Wu, Chin-chen ChangAbstract:In this paper, a novel VQ-based digital Image watermarking scheme is proposed. During the encoding process of the VQ compression technique, the proposed scheme embeds a representative digital watermark in the protected Image so that the watermark can be retrieved from the Image to effectively prove which party is in legal possession of the copyright in case an ownership dispute arises. In our method, the codewords in the VQ codebook are classified into different groups according to different characteristics and then each binary watermark bit is embedded into the selected VQ encoded block. The main feature of the proposed scheme is that the watermark exists both in the VQ Compressed Image and in the reconstructed Image after VQ decoding. Because the watermark is hidden inside the Compressed Image, which is much smaller in size, much transmission time and storage space can be saved when the Compressed data, instead of the original form, are transmitted over the Internet. Furthermore, the reconstructed Image has robustness against aggressive Image processing. The embedded watermark can even survive JPEG lossy compression.
