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access icon free Multi-frame super-resolution for long range captured iris polar image

© The Institution of Engineering and Technology
Received 20/05/2016, Accepted 25/10/2016, Revised 13/10/2016, Published 27/10/2016

In this study, a framework is proposed to super-resolve the long range captured iris polar images. In this study, modified diamond search and enhanced total variation algorithms are proposed to super-resolve the long range captured iris polar multi-frame images. The framework is tested on Chinese Academy of Sciences' Institute of Automation (CASIA) long range iris database by comparing and analysing the structural similarity index matrix, peak signal-to-noise ratio, visual information fidelity in pixel domain, and execution time of proposed algorithms with Yang and Nguyen state-of-the-art algorithms. The results demonstrate that the proposed framework is well suited for super-resolution of iris images captured at a long distance.

Inspec keywords: search problems; eye; image resolution; iris recognition

Other keywords: enhanced total variation algorithm; structural similarity index matrix analysis; visual information fidelity analysis; multiframe super-resolution; long range captured iris polar multiframe images; pixel domain; modified diamond search algorithm; peak signal-to-noise ratio analysis; execution time analysis; CASIA long range iris database; iris recognition

Subjects: Combinatorial mathematics; Optimisation techniques; Image recognition; Combinatorial mathematics; Computer vision and image processing techniques; Optimisation techniques

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