No-Reference Quality Evaluator of Transparently Encrypted Images

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No-Reference Quality Evaluator of Transparently Encrypted Images

Guanghui Yue; Chunping Hou; Ke Gu; Tianwei Zhou; Hantao Liu

In past years, various encrypted algorithms have been proposed to fully or partially protect the multimedia content in view of practical applications. In the context of digital TV broadcasting, transparent encryption only protects partial content and fulfills both security and quality requirements. To date, only a few reference-based works have been reported to evaluate the quality of transparently encrypted images. However, these works are incapable of reference-unavailable conditions. In this paper, we conduct the first attempt that proposes a novel quality evaluator in the absence of reference images. The key strategy of the proposed metric lies in extracting features by considering the motivation of transparently encrypted images. Specifically, given that encrypted images prevent content from being easily recognized, several features, including correlation coefficient, information entropy, and intensity statistic, are preliminarily extracted to estimate visual recognizability. Meanwhile, considering that encrypted images are avoided since they are of extremely low quality, we also capture many features to measure the distortions on multiple quality-sensitive image attributes, such as naturalness, structure, and texture. Finally, the quality evaluator is built by bridging all extracted features and corresponding quality scores via a regression module. Experimental results demonstrate that the proposed method is superior to the mainstream no-reference quality evaluation methods designed for synthetically distorted images and possesses a close approximation to state-of-the-art reference-based methods designed for encrypted images.

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