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Adaptive reversible data hiding for JPEG images with multiple two-dimensional histograms
Affiliation:1. College of Computer Science and Technology, Shanghai University of Electric Power, Shanghai, PR China;2. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai, PR China;3. Computer Science Department, University of Victoria, BC V8W 3P6, Canada;1. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;2. School of Mechanical Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China;3. Guangxi Key Lab of Multi-source Information Mining & Security, Guangxi Normal University, Guilin 541004, China;1. College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China;2. School of National Security and Counter Terrorism, People''s Public Security University of China, Beijing 100038, China;1. Department of Information Engineering and Computer Science, Feng Chia University, Taichung 407, Taiwan;2. Department of Electronic Engineering, National Quemoy University, Kinmen 892, Taiwan
Abstract:Joint photographic experts group (JPEG) can provide good quality with small file size but also eliminate extensively the redundancies of images. Therefore, hiding data into JPEG images in terms of maintaining high visual quality at small file sizes has been a great challenge for researchers. In this paper, an adaptive reversible data hiding method for JPEG images containing multiple two-dimensional (2D) histograms is proposed. Adaptability is mainly reflected in three aspects. The first one is to preferentially select sharper histograms for data embedding after K histograms are established by constructing the kth (k{1,2,,K}) histogram using the kth non-zero alternating current (AC) coefficient of all the quantized discrete cosine transform blocks. On the other hand, to fully exploit the strong correlation between coefficients of one histogram, the smoothness of each coefficient is estimated by a block smoothness estimator so that a sharply-distributed 2D-histogram is constructed by combining two coefficients with similar smoothness into a pair. The pair corresponding to low complexity is selected priorly for data embedding, leading to high embedding performance while maintaining low file size. Besides, we design multiple embedding strategies to adaptively select the embedding strategy for each 2D histogram. Experimental results demonstrate that the proposed method can achieve higher rate–distortion performance which maintaining lower file storage space, compared with previous studies.
Keywords:Reversible data hiding  Multiple histograms  Two-dimensional histogram  Rate–distortion model
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