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TURBULENCE DEGRADED IMAGES RESTORATION BASED ON IMPROVED MULTIFRAME ITERATIVE LOOPS AND DATA MINING

Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China

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TIANXU ZHANG

Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China

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BIYIN ZHANG

Institute for Pattern Recognition and Artificial Intelligence, Huazhong University of Science and Technology, Wuhan, 430074, P. R. China

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https://doi.org/10.1142/S0219467807002799Cited by:0 (Source: Crossref)

Abstract

In this paper a novel restoration algorithm based on iterative loops and data mining is proposed to restore the original object image from a few frames of aero-optics degraded images through the turbulence medium. Based on the iterative loops, the iterative mathematic models to estimate the random turbulent optical point spread functions and object image are built. A series of restoration experiments for both simulated and real aero-optics degraded images were performed to examine the proposed algorithm under a computerized simulation environment, which show that the proposed algorithm outperform previous algorithms and therefore is effective for practical applications.

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