Visual saliency-based confidentiality metric for selective crypto-compressed JPEG images

Noe Le Philippe 1 Vincent Itier 1 William Puech 1
1 ICAR - Image & Interaction
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
Abstract : For security reasons, more and more digital data are transferred or stored in encrypted domains. In particular for images , selective format-compliant JPEG encryption methods have been proposed for the last ten years. Since encryption is selective, in order to reduce the processing time and to be format-compliant, it is now necessary to evaluate the confidentiality of these selective crypto-compressed JPEG images. It is known that image quality metrics, such as PSNR or SSIM, give a very low correlation with a mean opinion score (MOS) for low quality images. In this paper, we propose an efficient confidentiality metric based on the visual saliency diffusion. We show experimentally that this metric is well correlated with a MOS and efficient to evaluate the confidentiality of selective crypto-compressed JPEG images.
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Noe Le Philippe, Vincent Itier, William Puech. Visual saliency-based confidentiality metric for selective crypto-compressed JPEG images. ICIP: International Conference on Image Processing, Sep 2017, Beijing, China. pp.4347-4351, ⟨10.1109/ICIP.2017.8297103⟩. ⟨lirmm-02023204⟩

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