基于模型的远红外图像增强

R. Highnam, M. Brady
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引用次数: 11

摘要

本文设计了一种鲁棒可靠的远红外图像增强算法。该算法基于成像过程模型。由于场景的不可预测性,我们开发的模型是定性的。该模型预测,理想的远红外图像由分段不变的小块组成。在此模型和退化因素模型的基础上,我们应用了两种已知的算法:中值滤波和空间同态滤波。为了加快增强速度,我们对模型进行了时间上的扩展,提出了一种新的算法:时空同态滤波。论文最后尝试将夜间拍摄的远红外线图像转换为可见的日光图像
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Model-based image enhancement of far infra-red images
In this paper we devise robust and reliable image enhancement algorithms for far infra-red images. The algorithms are based upon a model of the imaging process. The model that we develop is qualitative due to the unpredictable nature of the scenes. The model predicts that an idealized far infra-red image consists of piecewise-constant patches. On the basis of this model and models of the degrading factors we then apply two known algorithms: median filtering and spatial homomorphic filtering. In order to speed up the enhancement we extend our model temporally and develop a new algorithm: spatio-temporal homomorphic filtering. The paper ends with an attempt to convert the far infra-red images taken at night to visible daylight images
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