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A Multiresolution Approach to Image Enhancement Via Histogram Shaping and Adaptive Wiener Filtering

机译:通过直方图整形和自适应维纳滤波的多分辨率图像增强方法

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It is critical in military applications to be able to extract features in imagery that may be of interest to the viewer at any time of the day or night. Infrared (IR) imagery is ideally suited for producing these types of images. However, even under the best of circumstances, the traditional approach of applying a global automatic gain control (AGC) to the digital image may not provide the user with local area details that may be of interest. Processing the imagery locally can enhance additional features and characteristics in the image which provide the viewer with an improved understanding of the scene being observed. This paper describes a multi-resolution pyramid approach for decomposing an image, enhancing its contrast by remapping the histograms to desired pdfs, filtering them and recombining them to create an output image with much more visible detail than the input image. The technique improves the local area image contrast in light and dark areas providing the warfighter with significantly improved situational awareness.
机译:在军事应用中至关重要的是,能够在白天或晚上的任何时间提取观看者可能感兴趣的图像特征。红外(IR)图像非常适合生成这些类型的图像。但是,即使在最好的情况下,将全局自动增益控制(AGC)应用于数字图像的传统方法也可能无法为用户提供可能感兴趣的局部区域细节。局部处理图像可以增强图像中的其他特征和特性,从而使观看者可以更好地理解所观察的场景。本文介绍了一种用于分解图像的多分辨率金字塔方法,通过将直方图重新映射为所需的pdf,对其进行过滤和重新组合来增强其对比度,以创建比输入图像具有更多可见细节的输出图像。该技术改善了明暗区域的局部图像对比度,为战斗人员提供了明显改善的态势感知能力。

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