Visible to the public Biblio

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2017-03-08
Behjat-Jamal, S., Demirci, R., Rahkar-Farshi, T..  2015.  Hybrid bilateral filter. 2015 International Symposium on Computer Science and Software Engineering (CSSE). :1–6.

A variety of methods for images noise reduction has been developed so far. Most of them successfully remove noise but their edge preserving capabilities are weak. Therefore bilateral image filter is helpful to deal with this problem. Nevertheless, their performances depend on spatial and photometric parameters which are chosen by user. Conventionally, the geometric weight is calculated by means of distance of neighboring pixels and the photometric weight is calculated by means of color components of neighboring pixels. The range of weights is between zero and one. In this paper, geometric weights are estimated by fuzzy metrics and photometric weights are estimated by using fuzzy rule based system which does not require any predefined parameter. Experimental results of conventional, fuzzy bilateral filter and proposed approach have been included.

2017-02-14
K. Liu, M. Li, X. Li.  2015.  "Hiding Media Data via Shaders: Enabling Private Sharing in the Clouds". 2015 IEEE 8th International Conference on Cloud Computing. :122-129.

In the era of Cloud and Social Networks, mobile devices exhibit much more powerful abilities for big media data storage and sharing. However, many users are still reluctant to share/store their data via clouds due to the potential leakage of confidential or private information. Although some cloud services provide storage encryption and access protection, privacy risks are still high since the protection is not always adequately conducted from end-to-end. Most customers are aware of the danger of letting data control out of their hands, e.g., Storing them to YouTube, Flickr, Facebook, Google+. Because of substantial practical and business needs, existing cloud services are restricted to the desired formats, e.g., Video and photo, without allowing arbitrary encrypted data. In this paper, we propose a format-compliant end-to-end privacy-preserving scheme for media sharing/storage issues with considerations for big data, clouds, and mobility. To realize efficient encryption for big media data, we jointly achieve format-compliant, compression-independent and correlation-preserving via multi-channel chained solutions under the guideline of Markov cipher. The encryption and decryption process is integrated into an image/video filter via GPU Shader for display-to-display full encryption. The proposed scheme makes big media data sharing/storage safer and easier in the clouds.