Non-local Denoising in Encrypted Images

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• 作者：Xianjun Hu (17)
  Weiming Zhang (17)
  Honggang Hu (17)
  Nenghai Yu (17)
  
• 关键词：Paillier homomorphic encryption ; Image denoising ; Non ; Local Means ; Johnson ; Lindenstrauss Transform
• 刊名：Lecture Notes in Computer Science
• 出版年：2014
• 出版时间：2014
• 年：2014
• 卷：8662
• 期：1
• 页码：386-395
• 全文大小：1,307 KB
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• 作者单位：Xianjun Hu (17)
  Weiming Zhang (17)
  Honggang Hu (17)
  Nenghai Yu (17)
  
  17. Key Laboratory of Electromagnetic Space Information, Chinese Academy of Sciences, University of Science and Technology of China, Hefei, China, 230027
  
• ISSN：1611-3349

文摘

Signal processing in the encrypted domain becomes a desired technique to protect privacy of outsourced data in cloud. In this paper we propose a double-cipher scheme to implement non-local means denoising in encrypted images. In this scheme, one ciphertext is generated by Paillier scheme which enables the mean-filter, and the other is obtained by a privacy-preserving transform which enables the non-local searching. By the privacy-preserving transform, the cloud can search the similar pixel blocks in the ciphertexts with the same speed as in the plaintexts, so the proposed method can be fast executed. The experimental results show that the quality of denoised images in the encrypted domain is comparable to that obtained in plain domain.