Open AccessMulti‐frame super‐resolution for long range captured iris polar image
Author(s) -
Deshpande Anand,
Patavardhan Prashant
Publication year - 2017
Publication title -
iet biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.434
H-Index - 28
eISSN - 2047-4946
pISSN - 2047-4938
DOI - 10.1049/iet-bmt.2016.0076
Subject(s) - computer science , iris (biosensor) , artificial intelligence , computer vision , range (aeronautics) , iris recognition , frame (networking) , pixel , image (mathematics) , polar , pattern recognition (psychology) , biometrics , telecommunications , materials science , physics , astronomy , composite material
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.