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Abstract

The aim of image enhancement is to improve the interpretability or perception of information in images for human viewers, or to provide 'better' input for another automated image processing techniques. The Contrast Enhancement Turbulence Mitigation (CETM) techniques can manage the vagueness and ambiguity efficiently. Contrast enhancement is a powerful tool to represent and process human knowledge in form of image enhancement. The CETM algorithm enhances image contrast very effectively. Over the years, many researchers have provided insight into the physics of either the fog or turbulence but not both. Researchers have proposed methods to remove fog in images fast enough for real-time processing. In addition methods have been proposed by other researchers that address the atmospheric turbulence problem. In this paper, provide an analysis that incorporates both physics models: 1) fog and 2) turbulence. It is observed how contrast enhancements (fog removal) can affect image alignment and image averaging. In this paper, a new joint contrast enhancement and turbulence mitigation (CETM) method that utilizes estimations from the contrast enhancement algorithm to improve the turbulence removal algorithm. It provides a new turbulent mitigation object metric that measures temporal consistency.

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How to Cite
M.Pavithra Devi, T.Maragatham, & Karthik.S. (2015). EDGE PRESERVING GLOBAL CONSTRAST ENHANCEMENT FOR MULTISCALE TURBULENCE MITIGATION . International Journal of Intellectual Advancements and Research in Engineering Computations, 3(2), 80–84. Retrieved from https://ijiarec.com/ijiarec/article/view/1289