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Journal articles on the topic 'Prediction error expansion'

Author: Grafiati

Published: 5 June 2025

Last updated: 2 August 2025

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1

Bensebia, Bensaber, Fatma-Zohra Chaouche, Ouahida Bensebia, and Soumia Moustefaï. "Bed expansion in turbulent bed contactor: Experiments and prediction." Chemical Industry and Chemical Engineering Quarterly, no. 00 (2023): 10. http://dx.doi.org/10.2298/ciceq230304010b.

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In this work, the hydrodynamics of the turbulent bed contractor (TBC) have been studied in terms of bed expansion (Hd/Hst) using a particular approach for the prediction of this important property for the design of such equipment. The study is based on 1604 sets of experimental data of the bed expansion, obtained by varying the operating variables (gas velocity, liquid spray, packing characteristics, static bed height and free opening of the supporting grid. The prediction of the bed expansion necessitates the estimation of gas and liquid holdups. To achieve this, we employed a variety of corr

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Ni, Chengcai, and Lianjun Zhang. "An Estimator of Prediction Error Variance for Projection Equations." Forest Science 54, no. 6 (2008): 569–78. http://dx.doi.org/10.1093/forestscience/54.6.569.

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Abstract An estimator of prediction error variance for projection equations was derived using the first-order Taylor expansion in this study. The estimator, a modified estimator of the prediction error variance for a population mean regression model, was adapted for situations in which projection equations are applied to unsampled individuals. The estimator accounted for the errors associated with the response variable on the right side of a projection equation, as well as the errors associated with parameter estimation and serial correlations in data. The application of the estimator was demo

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Kong, Xiaoxi, Wenguang He, and Zhanchuan Cai. "A Novel High-Fidelity Reversible Data Hiding Method Based on Adaptive Multi-pass Embedding." Mathematics 13, no. 11 (2025): 1881. https://doi.org/10.3390/math13111881.

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In reversible data hiding, prediction error generation plays a crucial role, with pixel value ordering (PVO) standing out as a prediction method that achieves high fidelity. However, conventional PVO approaches select predicted pixels and their predictions independently, failing to fully exploit the inherent redundancy in ordered pixel sequences. This paper proposes a novel PVO-based prediction method that leverages the continuity and spatial correlation of ordering pixels. We first introduce a new prediction technique that exploits the redundancy of consecutive pixels. Our approach selects th

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Caciula, Ion, Henri George Coanda, and Dinu Coltuc. "Multiple moduli prediction error expansion reversible data hiding." Signal Processing: Image Communication 71 (February 2019): 120–27. http://dx.doi.org/10.1016/j.image.2018.11.005.

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Harati, Ehsan, and Hossein Ahmadi Noubari. "Long Time Prediction of Uncertain Systems Using Singular Perturbation." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 25, no. 05 (2017): 707–21. http://dx.doi.org/10.1142/s0218488517500301.

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This paper considers the problem of long time prediction of uncertain dynamic systems. Spectral methods such as polynomial chaos expansion (PCE) provides a suitable alternative for classical Monte Carlo method with lower computational load. However, polynomial chaos expansion has a major drawback of long time integration error. In this paper, we will apply singular perturbation (SP) method for reducing long time integration error. Using SP the accuracy of long time predictions are improved with comparable computational load. We will apply SP to illustrative exemplify problems to show effective

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Zeng, Xiao, Zhenyong Chen, Ming Chen, and Zhang Xiong. "Reversible Video Watermarking Based on Inter-prediction Error Expansion." Journal of Computer-Aided Design & Computer Graphics 22, no. 5 (2010): 871–78. http://dx.doi.org/10.3724/sp.j.1089.2010.10822.

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Ou, Bo, Xiaolong Li, Yao Zhao, Rongrong Ni, and Yun-Qing Shi. "Pairwise Prediction-Error Expansion for Efficient Reversible Data Hiding." IEEE Transactions on Image Processing 22, no. 12 (2013): 5010–21. http://dx.doi.org/10.1109/tip.2013.2281422.

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Roy, Aniket, and Rajat Subhra Chakraborty. "Toward Optimal Prediction Error Expansion-Based Reversible Image Watermarking." IEEE Transactions on Circuits and Systems for Video Technology 30, no. 8 (2020): 2377–90. http://dx.doi.org/10.1109/tcsvt.2019.2911042.

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Nguyen, Thai-Son, and Phuoc-Hung Vo. "Reversible image authentication scheme based on prediction error expansion." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 253. http://dx.doi.org/10.11591/ijeecs.v21.i1.pp253-262.

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<span>Reversible image authentication scheme is a technique that detects tampered areas in images and allows them to be reconstructed to their original version without any distortion. In this article, a new, reversible, image authentication scheme based on prediction error expansion is proposed for digital images. The proposed scheme classifies the host image into smooth blocks and complex blocks. Then, an authentication code that is created randomly with a seed is embedded adaptively into each image block. Experimental results showed that our proposed scheme achieves the high accuracy o

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10

Yu, Xiang, Xiang Wang, and Qingqi Pei. "Reversible watermarking based on multi-dimensional prediction-error expansion." Multimedia Tools and Applications 77, no. 14 (2018): 18085–104. http://dx.doi.org/10.1007/s11042-018-5794-y.

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Nguyen, Thai-Son, and Phuoc-Hung Vo. "Reversible image authentication scheme based on prediction error expansion." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 1 (2021): 253–62. https://doi.org/10.11591/ijeecs.v21.i1.pp253-262.

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Reversible image authentication scheme is a technique that detects tampered areas in images and allows them to be reconstructed to their original version without any distortion. In this article, a new, reversible, image authentication scheme based on prediction error expansion is proposed for digital images. The proposed scheme classifies the host image into smooth blocks and complex blocks. Then, an authentication code that is created randomly with a seed is embedded adaptively into each image block. Experimental results showed that our proposed scheme achieves the high accuracy of tamper det

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Lin, Jiang, Li Guolong, Wang Shilong, Xu Kai, and Li Zheyu. "Feed shaft thermal expansion error modeling based on principal component regression." Insights of Automation in Manufacturing 1, no. 1 (2024): 16–24. http://dx.doi.org/10.59782/iam.v1i1.202.

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In order to further improve the prediction accuracy of the thermal error model of the feed shaft of the gear grinding machine, this paper proposes a feed shaft thermal expansion error modeling method based on principal component regression. The feed shaft positioning error is decoupled by linear fitting to obtain the thermal expansion slope parameter, the position correlation of the feed shaft thermal expansion error is eliminated, and a regression model of the thermal expansion slope parameter and the temperature of all measuring points is established based on the principal component regressi

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13

Gao, Guangyong, Caixue Zhou, and Zongmin Cui. "Reversible Watermarking Using Prediction-Error Expansion and Extreme Learning Machine." Mathematical Problems in Engineering 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/670535.

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Currently, the research for reversible watermarking focuses on the decreasing of image distortion. Aiming at this issue, this paper presents an improvement method to lower the embedding distortion based on the prediction-error expansion (PE) technique. Firstly, the extreme learning machine (ELM) with good generalization ability is utilized to enhance the prediction accuracy for image pixel value during the watermarking embedding, and the lower prediction error results in the reduction of image distortion. Moreover, an optimization operation for strengthening the performance of ELM is taken to

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Xiang, Hongyin, Jinsha Yuan, and Sizu Hou. "Hybrid Predictor and Field-Biased Context Pixel Selection Based on PPVO." Mathematical Problems in Engineering 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/2585983.

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Most pixel-value-ordering (PVO) predictors generated prediction-errors including −1 and 1 in a block-by-block manner. Pixel-based PVO (PPVO) method provided a novel pixel scan strategy in a pixel-by-pixel way. Prediction-error bin 0 is expanded for embedding with the help of equalizing context pixels for prediction. In this paper, a PPVO-based hybrid predictor (HPPVO) is proposed as an extension. HPPVO predicts pixel in both positive and negative orientations. Assisted by expansion bins selection technique, this hybrid predictor presents an optimized prediction-error expansion strategy includi

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Lu, Chang, Jiyou Fei, Xing Zhao, and Xiongfei Shao. "Laser Cutting Thermal Error Prediction Method Based on Multivariate Segmentation." Journal of Physics: Conference Series 2541, no. 1 (2023): 012027. http://dx.doi.org/10.1088/1742-6596/2541/1/012027.

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Abstract With the increasing accuracy of manufacturing processing, laser cutting has become one of the best ways to cut thin-walled parts. A multivariate segmented thermal error prediction method is proposed for thermal errors in laser cutting. Based on actual processing data, we analyzed the thermal expansion of the material during the cutting process. Modeling simulation and heat deformation prediction are performed. W18Cr4V material was used as the study object for computational verification. The results show that multiple-segmented regression can achieve data accuracy of more than 90.4%. F

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16

李, 思雨. "Improved Reversible Data Hiding Algorithm for Pairwise Prediction Error Expansion." Computer Science and Application 11, no. 05 (2021): 1484–95. http://dx.doi.org/10.12677/csa.2021.115152.

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He, Wenguang, and Zhanchuan Cai. "Reversible Data Hiding Based on Dual Pairwise Prediction-Error Expansion." IEEE Transactions on Image Processing 30 (2021): 5045–55. http://dx.doi.org/10.1109/tip.2021.3078088.

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18

Qin, Chuan, Chin-Chen Chang, and Li-Ting Liao. "An adaptive prediction-error expansion oriented reversible information hiding scheme." Pattern Recognition Letters 33, no. 16 (2012): 2166–72. http://dx.doi.org/10.1016/j.patrec.2012.08.004.

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19

Wu, Guilin, Haisong Ang, and Qingxi Li. "Linear Proportional-Integral-Differential-Robustified Continuous-Time Optimal Predictive Control for a Class of Nonlinear Systems." Applied Sciences 12, no. 11 (2022): 5446. http://dx.doi.org/10.3390/app12115446.

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This paper presents a novel robust optimal predictive control approach for a class of nonlinear continuous-time systems perturbed by unknown disturbances. First, a new error state with a linear proportional-integral-differential (PID) structure considering current, accumulative, and derivative tracking errors is defined. Second, prediction of the error state within the predictive periods is expressed by the error state and its high-order derivatives according to the Taylor series expansion. Last, the proposed control law as well as the main result of this paper are derived by minimizing the pr

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20

Abramova, Valeriia, Arnau Oliver, Joaquim Salvi, Mikel Terceño, Yolanda Silva, and Xavier Lladó. "An End-to-End Deep Learning Framework for Predicting Hematoma Expansion in Hemorrhagic Stroke Patients from CT Images." Applied Sciences 14, no. 7 (2024): 2708. http://dx.doi.org/10.3390/app14072708.

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Hematoma expansion (HE) occurs in 20% of patients with hemorrhagic stroke within 24 h of onset, and it is associated with a poorer patient outcome. From a clinical point of view, predicting HE from the initial patient computed tomography (CT) image is useful to improve therapeutic decisions and minimize prognosis errors. In this work, we propose an end-to-end deep learning framework for predicting the final hematoma expansion and its corresponding lesion mask. We also explore the problem of having limited data and propose to augment the available dataset with synthetic images. The obtained res

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21

Yang, Fan, and Xinxia Li. "Construction of Prediction Model of Radiotherapy Set-Up Errors in Patients with Lung Cancer." BioMed Research International 2022 (June 25, 2022): 1–6. http://dx.doi.org/10.1155/2022/5642529.

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Objective. This study intends to construct an error distribution prediction model and analyze its parameters and analyzes the boundary size of CTV extension to PTV, so as to provide a reference for lung cancer patients to control clinical set-up errors and radiotherapy planning. Methods. The prior SBRT set-up error data of 50 patients with lung cancer treated by medical linear accelerator were selected, the Gaussian mixture model was adopted to construct the error distribution prediction model, and the model parameters were solved, based on which the emission boundary from CTV to PTV was calcu

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22

Wang, Fei, Zhaoxin Xie, and Zuo Chen. "High Capacity Reversible Watermarking for Audio by Histogram Shifting and Predicted Error Expansion." Scientific World Journal 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/656251.

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Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution

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23

Chi, Heng-Xiao, Ji-Hwei Horng, and Chin-Chen Chang. "Reversible Data Hiding Based on Pixel-Value-Ordering and Prediction-Error Triplet Expansion." Mathematics 9, no. 14 (2021): 1703. http://dx.doi.org/10.3390/math9141703.

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Pixel value ordering and prediction error expansion (PVO+PEE) is a very successful reversible data hiding (RDH) scheme. A series of studies were proposed to improve the performance of the PVO-based scheme. However, the embedding capacity of those schemes is quite limited. We propose a two-step prediction-error-triplet expansion RDH scheme based on PVO. A three-dimensional state transition map for the prediction-error triplet is also proposed to guide the embedding of the two-step scheme. By properly designing the state transitions, the proposed scheme can embed secret data or expand without em

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24

Li, Li, Shengxian Wang, Ting Luo, Ching-Chun Chang, Qili Zhou, and Hui Li. "Reversible Data Hiding for Encrypted 3D Model Based on Prediction Error Expansion." Journal of Sensors 2020 (September 1, 2020): 1–14. http://dx.doi.org/10.1155/2020/8851999.

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Since 3D models can intuitively display real-world information, there are potential scenarios in many application fields, such as architectural models and medical organ models. However, a 3D model shared through the internet can be easily obtained by an unauthorized user. In order to solve the security problem of 3D model in the cloud, a reversible data hiding method for encrypted 3D model based on prediction error expansion is proposed. In this method, the original 3D model is preprocessed, and the vertex of 3D model is encrypted by using the Paillier cryptosystem. In the cloud, in order to i

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Lee, Suk-Hwan, Seong-Geun Kwon, and Ki-Ryong Kwon. "Least Square Prediction Error Expansion Based Reversible Watermarking for DNA Sequence." Journal of the Institute of Electronics and Information Engineers 52, no. 11 (2015): 66–78. http://dx.doi.org/10.5573/ieie.2015.52.11.066.

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26

Lee, Chin-Feng, Chi-Yao Weng, and Cheng-Yu Kao. "Reversible data hiding using Lagrange interpolation for prediction-error expansion embedding." Soft Computing 23, no. 19 (2018): 9719–31. http://dx.doi.org/10.1007/s00500-018-3537-7.

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KURIBAYASHI, M., M. MORII, and H. TANAKA. "Reversible Watermark with Large Capacity Based on the Prediction Error Expansion." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E91-A, no. 7 (2008): 1780–90. http://dx.doi.org/10.1093/ietfec/e91-a.7.1780.

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Kumar, Manoj, and Smita Agrawal. "Reversible data hiding based on prediction error expansion using adjacent pixels." Security and Communication Networks 9, no. 16 (2016): 3703–12. http://dx.doi.org/10.1002/sec.1575.

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Yun, Seok-Teak, and Seung-Hyun Kong. "Forecasting Methods of Battery Charge and Discharge Current Profile for LEO Satellites." Electronics 10, no. 23 (2021): 2999. http://dx.doi.org/10.3390/electronics10232999.

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The orbital characteristics of low Earth orbit (LEO) satellite systems prevent continuous monitoring because ground access time is limited. For this reason, the development of simulators for predicting satellite states for the entire orbit is required. Power-related prediction is one of the important LEO satellite simulations because it is directly related to the lifespan and mission of the satellite. Accurate predictions of the charge and discharge current of a power system’s battery are essential for fault management design, mission design, and expansion of LEO satellites. However, it is dif

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Ding, Xianfeng, Dan Qu, and Haiyan Qiu. "A New Production Prediction Model Based on Taylor Expansion Formula." Mathematical Problems in Engineering 2018 (December 3, 2018): 1–12. http://dx.doi.org/10.1155/2018/1369639.

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On the basis of the analysis of the cumulative production growth curve model, the model variables are adjusted, and the Taylor formula is expanded on the adjusted model. Then the appropriate expansion order n is selected, and the new model for the prediction of cumulative production is established. Furthermore, the error of the new model is discussed, and the model can theoretically achieve any given precision. The model can forecast oil and gas production, cumulative production, and recoverable reserves. Finally, the example analyses show that the greater the order number (n) is, the smaller

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Hamadou, Ali, Lanciné Camara, Abdoul Aziz Issaka Hassane, and Harouna Naroua. "Reversible Fragile Watermarking Scheme for Relational Database Based on Prediction-Error Expansion." Mathematical Problems in Engineering 2020 (May 5, 2020): 1–9. http://dx.doi.org/10.1155/2020/1740205.

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The protection of database systems content using digital watermarking is nowadays an emerging research direction in information security. In the literature, many solutions have been proposed either for copyright protection and ownership proofing or integrity checking and tamper localization. Nevertheless, most of them are distortion embedding based as they introduce permanent errors into the cover data during the encoding process, which inevitably affect data quality and usability. Since such distortions are not tolerated in many applications, including banking, medical, and military data, rev

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Biscarini, Andrea. "Simulating the Fast Prediction Strategy of the Sensorimotor System." Biomimetics 6, no. 1 (2021): 14. http://dx.doi.org/10.3390/biomimetics6010014.

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The values of a physiological parameter and its time derivatives, detected at different times by different sensory receptors, are processed by the sensorimotor system to predict the time evolution of the parameter and convey appropriate control commands acting with minimum latency (few milliseconds) from the sensory stimulus. We have derived a power-series expansion (U-expansion) to simulate the fast prediction strategy of the sensorimotor system. Given a time-function f, a time-instant t0, and a time-increment ττ, the U-expansion enables the calculation of τf(t0+τ) from f(t0) and the values f

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Pan, I.-Hui, Ping-Sheng Huang, Te-Jen Chang, and Hsiang-Hsiung Chen. "Multilayer Reversible Information Hiding with Prediction-Error Expansion and Dynamic Threshold Analysis." Sensors 22, no. 13 (2022): 4872. http://dx.doi.org/10.3390/s22134872.

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The rapid development of internet and social media has driven the great requirement for information sharing and intelligent property protection. Therefore, reversible information embedding theory has marked some approaches for information security. Assuming reversibility, the original and embedded data must be completely restored. In this paper, a high-capacity and multilayer reversible information hiding technique for digital images was presented. First, the integer Haar wavelet transform scheme converted the cover image from the spatial into the frequency domain that was used. Furthermore, w

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XIONG, Zhi-yong, and Tian-fa JIANG. "Lossless data hiding for color images based on prediction error difference expansion." Journal of Computer Applications 30, no. 1 (2010): 186–89. http://dx.doi.org/10.3724/sp.j.1087.2010.00186.

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XIONG, Zhi-yong, and Jiang-qing WANG. "Reversible data hiding based on prediction error difference expansion and LSB replacement." Journal of Computer Applications 30, no. 4 (2010): 909–13. http://dx.doi.org/10.3724/sp.j.1087.2010.00909.

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XIONG, Zhi-yong, and Jiang-qing WANG. "Reversible data hiding based on prediction error difference expansion of ternary components." Journal of Computer Applications 30, no. 9 (2010): 2408–12. http://dx.doi.org/10.3724/sp.j.1087.2010.02408.

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C., Vinoth Kumar, and Natarajan V. "Hybrid local prediction error-based difference expansion reversible watermarking for medical images." Computers & Electrical Engineering 53 (July 2016): 333–45. http://dx.doi.org/10.1016/j.compeleceng.2015.11.033.

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Xiaolong Li, Bin Yang, and Tieyong Zeng. "Efficient Reversible Watermarking Based on Adaptive Prediction-Error Expansion and Pixel Selection." IEEE Transactions on Image Processing 20, no. 12 (2011): 3524–33. http://dx.doi.org/10.1109/tip.2011.2150233.

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Ou, Bo, Xiaolong Li, Yao Zhao, and Rongrong Ni. "Reversible data hiding using invariant pixel-value-ordering and prediction-error expansion." Signal Processing: Image Communication 29, no. 7 (2014): 760–72. http://dx.doi.org/10.1016/j.image.2014.05.003.

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Ko, Chan-Bin, and Joon-Ho Lee. "Performance Analysis of Interferometer Algorithm under Phase Measurement Error." Applied Sciences 11, no. 2 (2021): 467. http://dx.doi.org/10.3390/app11020467.

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Direction finding has been extensively studied over the past decades and a number of algorithms have been developed. In direction finding, theoretic performance prediction is a fundamental problem. This paper addresses the performance analysis issue of interferometer-based 2D angle of arrival estimation using uniform circular array (UCA). We propose an analytic method for performance analysis of interferometer in the presence of Gaussian or uniform error in phase measurement of incident signal on each sensor. The analytic mean square error (MSE), which is approximately equal to the MSE of actu

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Li, Z. Y., G. Tao, B. X. Ren, and X. F. Wang. "A Chamber Pressure Prediction Method Based on Strain Measurement of Composite Barrel Recoilless Guns." Journal of Physics: Conference Series 2460, no. 1 (2023): 012117. http://dx.doi.org/10.1088/1742-6596/2460/1/012117.

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Abstract To predict the chamber pressure of positions corresponding to the strain data of the gun barrel’ outside walls, this study measures the chamber pressure and strain of different positions in a recoilless gun, and proposes a chamber pressure calculation method which is based on strain measurement of cylinder walls using the single-layer thin-walled cylinder theory and the plane strain-elastic stress solution for multi-layer orthotropic cylinders. Experimental results showed that the deformation of the recoilless gun at different positions was caused by varying factors. Specifically, cha

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Panda, Niranjan, Twinkle Singh, and Shrabanee Swagatika. "ANN based modeling for stock market prediction." Journal of Statistics & Management Systems 26, no. 1 (2023): 87–100. http://dx.doi.org/10.47974/jsms-949.

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Analyzing stock market data and using recent developed algorithms for predicting the changes and forecasting the results is a difficult task nowaday. An efficient and faster method for selecting appropriate stock price improves market value as well as helps investors for benefits. In this paper new method implementing state of the art Artificial Neural Networks (ANNs) known as Legendre Neural Network (LENN) and Chebyshev Functional Link based Artificial Neural Network (CHFLANN) has been described and used for the analysis of stock market data. The process has been efficiently implemented in MA

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Dankorpho, Prathana. "Sales Forecasting for Retail Business using XGBoost Algorithm." Journal of Computer Science and Technology Studies 6, no. 2 (2024): 136–41. http://dx.doi.org/10.32996/jcsts.2024.6.2.15.

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The retail industry is continuously evolving with the expansion of sales channels and the diversification of product assortments. However, current forecasting methods, relying on simplistic statistical models, frequently encounter difficulties in adjusting to the dynamic retail environment. This limitation leads to challenges in accurately predicting sales volumes and frequencies. Consequently, there is a critical need to improve the accuracy and frequency of sales predictions to enable timely decision-making for business strategies. Through a comprehensive analysis of datasets spanning from 2

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Dong, Pengfei, Guochang Ye, Mehmet Kaya, and Linxia Gu. "Simulation-Driven Machine Learning for Predicting Stent Expansion in Calcified Coronary Artery." Applied Sciences 10, no. 17 (2020): 5820. http://dx.doi.org/10.3390/app10175820.

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In this work, we integrated finite element (FE) method and machine learning (ML) method to predict the stent expansion in a calcified coronary artery. The stenting procedure was captured in a patient-specific artery model, reconstructed based on optical coherence tomography images. Following FE simulation, eight geometrical features in each of 120 cross sections in the pre-stenting artery model, as well as the corresponding post-stenting lumen area, were extracted for training and testing the ML models. A linear regression model and a support vector regression (SVR) model with three different

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Abdul Wahed, Md, and Hussain Nyeem. "Reversible data hiding with dual pixel-value-ordering and minimum prediction error expansion." PLOS ONE 17, no. 8 (2022): e0271507. http://dx.doi.org/10.1371/journal.pone.0271507.

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Pixel Value Ordering (PVO) holds an impressive property for high fidelity Reversible Data Hiding (RDH). In this paper, we introduce a dual PVO (dPVO) for Prediction Error Expansion (PEE), and thereby develop a new RDH scheme to offer a better rate-distortion performance. Particularly, we propose to embed in two phases: forward and backward. In the forward phase, PVO with classic PEE is applied to every non-overlapping image block of size 1 × 3. In the backward phase, minimum-set and maximum-set of pixels are determined from the pixels predicted in the forward phase. The minimum set only contai

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Motomura, Ryota, Shoko Imaizumi, and Hitoshi Kiya. "A Reversible Data-Hiding Method with Prediction-Error Expansion in Compressible Encrypted Images." Applied Sciences 12, no. 19 (2022): 9418. http://dx.doi.org/10.3390/app12199418.

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This paper proposes a novel reversible data-hiding method in encrypted images to achieve both a high hiding capacity and good compression performance. The proposed method can also decrypt marked encrypted images without data extraction, so marked images containing a payload can be derived from marked encrypted images. A perceptual encryption algorithm proposed for an encryption-then-compression framework is used to generate compressible encrypted images. In addition, a predictor with high accuracy and a prediction-error expansion and histogram shifting method are used for data hiding. Conseque

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Liu, Chiang-Lung, and Tai-Hung Lai. "Novel Prediction Error Expansion-Based Data Hiding Scheme Using Effective Bin Search Algorithm." Advanced Science Letters 8, no. 1 (2012): 801–6. http://dx.doi.org/10.1166/asl.2012.2477.

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He, Wenguang, Ke Zhou, Jie Cai, Long Wang, and Gangqiang Xiong. "Reversible data hiding using multi-pass pixel value ordering and prediction-error expansion." Journal of Visual Communication and Image Representation 49 (November 2017): 351–60. http://dx.doi.org/10.1016/j.jvcir.2017.10.001.

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Weng, Chi-Yao. "DWT-based reversible information hiding scheme using prediction-error-expansion in multimedia images." Peer-to-Peer Networking and Applications 13, no. 2 (2019): 514–23. http://dx.doi.org/10.1007/s12083-018-0709-2.

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Yi, Shuang, Yicong Zhou, and Zhongyun Hua. "Reversible data hiding in encrypted images using adaptive block-level prediction-error expansion." Signal Processing: Image Communication 64 (May 2018): 78–88. http://dx.doi.org/10.1016/j.image.2018.03.001.

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