Temporal resolution enhancement of image sequences capturing evolving weather phenomena

I. Yanovsky, B. Lambrigtsen
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引用次数: 1

Abstract

In this paper, we develop an approach for temporal resolution enhancement of blurry and distorted image sequences capturing evolving weather phenomena. We first enhance the spatial resolution of a sequence of images using an efficient deconvolution method which we showed to reduce image ringing, blurring, and distortion, while sharpening the image and preserving information content. Such methodology is based on current research in sparse optimization and compressed sensing, which lead to unprecedented efficiencies for solving image reconstruction problems. We then consider the evolving sequence to be embedded in a deformable medium, and enhance temporal resolution of a sequence using nonlinear viscous fluid registration model. The physical continuum equation is solved using an efficient multigrid full approximation scheme.
时间分辨率增强图像序列捕捉不断变化的天气现象
在本文中,我们开发了一种方法,用于时间分辨率增强的模糊和扭曲的图像序列捕捉不断变化的天气现象。我们首先使用一种有效的反卷积方法来增强一系列图像的空间分辨率,我们展示了这种方法可以减少图像的环形、模糊和失真,同时锐化图像并保留信息内容。这种方法是基于目前在稀疏优化和压缩感知方面的研究,这些研究为解决图像重建问题带来了前所未有的效率。然后,我们考虑将演化序列嵌入到可变形介质中,并使用非线性粘性流体配准模型提高序列的时间分辨率。采用高效的多网格全近似格式求解物理连续介质方程。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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