A New Encryption-Then-Compression Scheme on Gray Images Using the Markov Random Field

• 作者: Chuntao Wang Goo-Rak Kwon Hao Xie Tianzheng Li Yang Feng
• 来源期刊: 计算机、材料和连续体(英文)
• 学科: 工学
• 关键词: Encryption-then-compression compressing encrypted image MARKOV RANDOM field compression efficiency factor graph.
• 年，卷（期）: 2018,（7）
• 页码范围: 107-121
• 页数: 15页
• 分类号: TP3

摘要

Compressing encrypted images remains a challenge.As illustrated in our previous work on compression of encrypted binary images,it is preferable to exploit statistical characteristics at the receiver.Through this line,we characterize statistical correlations between adjacent bitplanes of a gray image with the Markov random field(MRF),represent it with a factor graph,and integrate the constructed MRF factor graph in that for binary image reconstruction,which gives rise to a joint factor graph for gray images reconstruction(JFGIR).By exploiting the JFGIR at the receiver to facilitate the reconstruction of the original bitplanes and deriving theoretically the sum-product algorithm(SPA)adapted to the JFGIR,a novel MRF-based encryption-then-compression(ETC)scheme is thus proposed.After preferable universal parameters of the MRF between adjacent bitplanes are sought via a numerical manner,extensive experimental simulations are then carried out to show that the proposed scheme successfully compresses the first 3 and 4 most significant bitplanes(MSBs)for most test gray images and the others with a large portion of smooth area,respectively.Thus,the proposed scheme achieves significant improvement against the state-of-the-art leveraging the 2-D Markov source model at the receiver and is comparable or somewhat inferior to that using the resolution-progressive strategy in recovery.