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In this paper, a reversible data hiding method in encrypted image (RDHEI) is proposed. Prior to image encryption, the embeddable pixels are selected from an original image according to prediction errors due to adjacent pixels with strong correlation. Then the embeddable pixels and the other pixels are both rearranged and encrypted to generate an encrypted image. Secret bits are directly embedded into the multiple MSBs (most significant bit) of the embeddable pixels in the encrypted image to generate a marked encrypted image during the encoding phase. In the decoding phase, secret bits can be extracted from the multiple MSBs of the embeddable pixels in the marked encrypted image. Moreover, the original embeddable pixels are restored losslessly by using correlation of the adjacent pixels. Thus, a reconstructed image with high visual quality can be obtained only when the encryption key is available. Since exploiting multiple MSBs of the embeddable pixels, the proposed method can obtain a very large embedding capacity. Experimental results show that the proposed method is able to achieve an average embedding rate as large as 1.7215 bpp (bits per pixel) for the BOW-2 database.
Dewang Wang; Xianquan Zhang; Chunqiang Yu; Zhenjun Tang. Reversible Data Hiding in Encrypted Image Based on Multi-MSB Embedding Strategy. Applied Sciences 2020, 10, 2058 .
AMA StyleDewang Wang, Xianquan Zhang, Chunqiang Yu, Zhenjun Tang. Reversible Data Hiding in Encrypted Image Based on Multi-MSB Embedding Strategy. Applied Sciences. 2020; 10 (6):2058.
Chicago/Turabian StyleDewang Wang; Xianquan Zhang; Chunqiang Yu; Zhenjun Tang. 2020. "Reversible Data Hiding in Encrypted Image Based on Multi-MSB Embedding Strategy." Applied Sciences 10, no. 6: 2058.
Zhenjun Tang; Hewang Nie; Chi-Man Pun; Heng Yao; Chunqiang Yu; Xianquan Zhang. Color Image Reversible Data Hiding With Double-Layer Embedding. IEEE Access 2020, 8, 6915 -6926.
AMA StyleZhenjun Tang, Hewang Nie, Chi-Man Pun, Heng Yao, Chunqiang Yu, Xianquan Zhang. Color Image Reversible Data Hiding With Double-Layer Embedding. IEEE Access. 2020; 8 ():6915-6926.
Chicago/Turabian StyleZhenjun Tang; Hewang Nie; Chi-Man Pun; Heng Yao; Chunqiang Yu; Xianquan Zhang. 2020. "Color Image Reversible Data Hiding With Double-Layer Embedding." IEEE Access 8, no. : 6915-6926.
In this paper, we propose a separable reversible data hiding method in encrypted image (RDHEI) based on two-dimensional permutation and exploiting modification direction (EMD). The content owner uses two-dimensional permutation to encrypt original image through encryption key, which provides confidentiality for the original image. Then the data hider divides the encrypted image into a series of non-overlapping blocks and constructs histogram of adjacent encrypted pixel errors. Secret bits are embedded into a series of peak points of the histogram through EMD. Direct decryption, data extraction and image recovery can be performed separately by the receiver according to the availability of encryption key and data-hiding key. Different from some state-of-the-art RDHEI methods, visual quality of the directly decrypted image can be further improved by the receiver holding the encryption key. Experimental results demonstrate that the proposed method outperforms some state-of-the-art methods in embedding capacity and visual quality.
Chunqiang Yu; Chenmei Ye; Xianquan Zhang; Zhenjun Tang; Shanhua Zhan. Separable Reversible Data Hiding in Encrypted Image Based on Two-Dimensional Permutation and Exploiting Modification Direction. Mathematics 2019, 7, 976 .
AMA StyleChunqiang Yu, Chenmei Ye, Xianquan Zhang, Zhenjun Tang, Shanhua Zhan. Separable Reversible Data Hiding in Encrypted Image Based on Two-Dimensional Permutation and Exploiting Modification Direction. Mathematics. 2019; 7 (10):976.
Chicago/Turabian StyleChunqiang Yu; Chenmei Ye; Xianquan Zhang; Zhenjun Tang; Shanhua Zhan. 2019. "Separable Reversible Data Hiding in Encrypted Image Based on Two-Dimensional Permutation and Exploiting Modification Direction." Mathematics 7, no. 10: 976.
Image encryption is a useful technique of image content protection. In this paper, we propose a novel image encryption algorithm by jointly exploiting random overlapping block partition, double spiral scans, Henon chaotic map, and Lü chaotic map. Specifically, the input image is first divided into overlapping blocks and pixels of every block are scrambled via double spiral scans. During spiral scans, the start-point is randomly selected under the control of Henon chaotic map. Next, image content based secret keys are generated and used to control the Lü chaotic map for calculating a secret matrix with the same size of input image. Finally, the encrypted image is obtained by calculating XOR operation between the corresponding elements of the scrambled image and the secret matrix. Experimental result shows that the proposed algorithm has good encrypted results and outperforms some popular encryption algorithms.
Zhenjun Tang; Ye Yang; Shijie Xu; Chunqiang Yu; Xianquan Zhang. Image Encryption with Double Spiral Scans and Chaotic Maps. Security and Communication Networks 2019, 2019, 1 -15.
AMA StyleZhenjun Tang, Ye Yang, Shijie Xu, Chunqiang Yu, Xianquan Zhang. Image Encryption with Double Spiral Scans and Chaotic Maps. Security and Communication Networks. 2019; 2019 ():1-15.
Chicago/Turabian StyleZhenjun Tang; Ye Yang; Shijie Xu; Chunqiang Yu; Xianquan Zhang. 2019. "Image Encryption with Double Spiral Scans and Chaotic Maps." Security and Communication Networks 2019, no. : 1-15.
Reversible data hiding is an important topic of data hiding. This paper proposes a novel separable and error-free reversible data hiding in an encrypted image based on two-layer pixel errors. Specifically, the proposed scheme divides the original image into a series of non-overlapped blocks and permutes these blocks. Then, a closed Hilbert curve is used for scanning each block to obtain a one-dimensional pixel sequence. The pixels of the sequence are encrypted with key transmission. During data hiding, each non-overlapped block of the encrypted image is scanned in the closed Hilbert order to generate a one-dimensional encrypted pixel sequence. Finally, it exploits the histogram of two-layer adjacent encrypted pixel errors to embed secret data by histogram shifting and generate a marked encrypted image. Many experiments are carried out, and the results demonstrate that the proposed scheme reaches a high payload and outperforms some reversible data hiding schemes in the encrypted image.
Chunqiang Yu; Xianquan Zhang; Zhenjun Tang; Xiaojun Xie; Andxiaojun Xie. Separable and Error-Free Reversible Data Hiding in Encrypted Image Based on Two-Layer Pixel Errors. IEEE Access 2018, 6, 76956 -76969.
AMA StyleChunqiang Yu, Xianquan Zhang, Zhenjun Tang, Xiaojun Xie, Andxiaojun Xie. Separable and Error-Free Reversible Data Hiding in Encrypted Image Based on Two-Layer Pixel Errors. IEEE Access. 2018; 6 ():76956-76969.
Chicago/Turabian StyleChunqiang Yu; Xianquan Zhang; Zhenjun Tang; Xiaojun Xie; Andxiaojun Xie. 2018. "Separable and Error-Free Reversible Data Hiding in Encrypted Image Based on Two-Layer Pixel Errors." IEEE Access 6, no. : 76956-76969.
Data hiding in encrypted image is a recent popular topic of data security. In this paper, we propose a reversible data hiding algorithm with pixel prediction and additive homomorphism for encrypted image. Specifically, the proposed algorithm applies pixel prediction to the input image for generating a cover image for data embedding, referred to as the preprocessed image. The preprocessed image is then encrypted by additive homomorphism. Secret data is finally embedded into the encrypted image via modular 256 addition. During secret data extraction and image recovery, addition homomorphism and pixel prediction are jointly used. Experimental results demonstrate that the proposed algorithm can accurately recover original image and reach high embedding capacity and good visual quality. Comparisons show that the proposed algorithm outperforms some recent algorithms in embedding capacity and visual quality.
Chunqiang Yu; Xianquan Zhang; Zhenjun Tang; Yan Chen; Jingyu Huang. Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image. Security and Communication Networks 2018, 2018, 1 -13.
AMA StyleChunqiang Yu, Xianquan Zhang, Zhenjun Tang, Yan Chen, Jingyu Huang. Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image. Security and Communication Networks. 2018; 2018 ():1-13.
Chicago/Turabian StyleChunqiang Yu; Xianquan Zhang; Zhenjun Tang; Yan Chen; Jingyu Huang. 2018. "Reversible Data Hiding with Pixel Prediction and Additive Homomorphism for Encrypted Image." Security and Communication Networks 2018, no. : 1-13.
We propose a novel perceptual image hashing based on weighted discrete wavelet transform (DWT) statistical features. This hashing converts input image into a normalized image by bi-linear interpolation and color space conversion, extracts edge image of the normalized image via Canny operator, and divides the edge image into non-overlapping blocks. For each block, a three-level 2D DWT is applied to obtain different sub-bands and the weighted sum of the DWT statistics of these sub-bands is calculated. Finally, image hash is generated by concatenating and quantizing these weighted DWT features. Similarity of image hashes is measured by Euclidean distance. The Copydays dataset and the Uncompressed Color Image Database (UCID) are both used to evaluate classification between robustness and discrimination. Receiver operating characteristics curve comparisons illustrate that our hashing is superior to some state-of-the-art algorithms in classification performance with respect to robustness and discrimination. The LIVE Image Quality Assessment Database is used to validate our application in reduced-reference image quality assessment. Experimental results show that our hashing has better performance in image quality assessment than two popular measures, i.e. peak signal-to-noise ratio and structural similarity.
Zhenjun Tang; Ziqing Huang; Heng Yao; Xianquan Zhang; Lv Chen; Chunqiang Yu. Perceptual Image Hashing with Weighted DWT Features for Reduced-Reference Image Quality Assessment. The Computer Journal 2018, 61, 1695 -1709.
AMA StyleZhenjun Tang, Ziqing Huang, Heng Yao, Xianquan Zhang, Lv Chen, Chunqiang Yu. Perceptual Image Hashing with Weighted DWT Features for Reduced-Reference Image Quality Assessment. The Computer Journal. 2018; 61 (11):1695-1709.
Chicago/Turabian StyleZhenjun Tang; Ziqing Huang; Heng Yao; Xianquan Zhang; Lv Chen; Chunqiang Yu. 2018. "Perceptual Image Hashing with Weighted DWT Features for Reduced-Reference Image Quality Assessment." The Computer Journal 61, no. 11: 1695-1709.
The minimum vertex cover problem (MVCP) and minimum weighted vertex cover problem (MWVCP) have been used in a variety of applications. This paper focuses on a view of test-cost-sensitive rough set for MWVCP. We first provide a method to convert a minimum weight vertex cover of a graph into a minimal test cost attribute reduct of a test-cost-sensitive decision table. Then, an induced test-cost-sensitive decision table from an undirected weighted graph is established. On the foundation of the induced decision table, an improved heuristic algorithm for finding minimum weight vertex covers is proposed, it can avoid a mass of redundant computation. Furthermore, to improve efficiency, a quantum-behaved particle swarm optimization with immune mechanism is presented, which can avoid the phenomenon of premature, improve the global searching ability, and enhance the convergence speed. The results of the experiment show the advantages and limitations of the proposed algorithms compared with state-of-the-art algorithms.
Xiaojun Xie; Xiaolin Qin; Chunqiang Yu; Xingye Xu. Test-cost-sensitive rough set based approach for minimum weight vertex cover problem. Applied Soft Computing 2018, 64, 423 -435.
AMA StyleXiaojun Xie, Xiaolin Qin, Chunqiang Yu, Xingye Xu. Test-cost-sensitive rough set based approach for minimum weight vertex cover problem. Applied Soft Computing. 2018; 64 ():423-435.
Chicago/Turabian StyleXiaojun Xie; Xiaolin Qin; Chunqiang Yu; Xingye Xu. 2018. "Test-cost-sensitive rough set based approach for minimum weight vertex cover problem." Applied Soft Computing 64, no. : 423-435.
Zhenjun Tang; Quanfeng Lu; Huan Lao; Chunqiang Yu; Xianquan Zhang. Error-free reversible data hiding with high capacity in encrypted image. Optik 2018, 157, 750 -760.
AMA StyleZhenjun Tang, Quanfeng Lu, Huan Lao, Chunqiang Yu, Xianquan Zhang. Error-free reversible data hiding with high capacity in encrypted image. Optik. 2018; 157 ():750-760.
Chicago/Turabian StyleZhenjun Tang; Quanfeng Lu; Huan Lao; Chunqiang Yu; Xianquan Zhang. 2018. "Error-free reversible data hiding with high capacity in encrypted image." Optik 157, no. : 750-760.
Xianquan Zhang; Feng Ding; Zhenjun Tang; Chunqiang Yu. Salt and pepper noise removal with image inpainting. AEU - International Journal of Electronics and Communications 2015, 69, 307 -313.
AMA StyleXianquan Zhang, Feng Ding, Zhenjun Tang, Chunqiang Yu. Salt and pepper noise removal with image inpainting. AEU - International Journal of Electronics and Communications. 2015; 69 (1):307-313.
Chicago/Turabian StyleXianquan Zhang; Feng Ding; Zhenjun Tang; Chunqiang Yu. 2015. "Salt and pepper noise removal with image inpainting." AEU - International Journal of Electronics and Communications 69, no. 1: 307-313.
Zhenjun Tang; Xianquan Zhang; Chunqiang Yu; Dan He. Efficient point pattern matching algorithm for planar point sets under transform of translation, rotation and scale. Applied Mathematics and Computation 2014, 232, 624 -631.
AMA StyleZhenjun Tang, Xianquan Zhang, Chunqiang Yu, Dan He. Efficient point pattern matching algorithm for planar point sets under transform of translation, rotation and scale. Applied Mathematics and Computation. 2014; 232 ():624-631.
Chicago/Turabian StyleZhenjun Tang; Xianquan Zhang; Chunqiang Yu; Dan He. 2014. "Efficient point pattern matching algorithm for planar point sets under transform of translation, rotation and scale." Applied Mathematics and Computation 232, no. : 624-631.
Xianquan Zhang -; Shaomin Xie -; Chunqiang Yu -. Watermarking Algorithm for Resisting Cropping Attack Based on Haar Wavelet Transform. Journal of Convergence Information Technology 2012, 7, 174 -181.
AMA StyleXianquan Zhang -, Shaomin Xie -, Chunqiang Yu -. Watermarking Algorithm for Resisting Cropping Attack Based on Haar Wavelet Transform. Journal of Convergence Information Technology. 2012; 7 (7):174-181.
Chicago/Turabian StyleXianquan Zhang -; Shaomin Xie -; Chunqiang Yu -. 2012. "Watermarking Algorithm for Resisting Cropping Attack Based on Haar Wavelet Transform." Journal of Convergence Information Technology 7, no. 7: 174-181.