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Morphological Background Detection and Enhancement of Images With Poor Lighting

机译:光线不足的图像的形态学背景检测和增强

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摘要

In this paper, some morphological transformations are used to detect the background in images characterized by poor lighting. Lately, contrast image enhancement has been carried out by the application of two operators based on the Weber's law notion. The first operator employs information from block analysis, while the second transformation utilizes the opening by reconstruction, which is employed to define the multibackground notion. The objective of contrast operators consists in normalizing the grey level of the input image with the purpose of avoiding abrupt changes in intensity among the different regions. Finally, the performance of the proposed operators is illustrated through the processing of images with different backgrounds, the majority of them with poor lighting conditions.
机译:在本文中,使用一些形态学转换来检测光线不足的图像中的背景。最近,通过基于韦伯定律概念的两个运算符的应用,进行了对比度图像增强。第一个运算符使用来自块分析的信息,而第二个变换则使用通过重建的开孔,该开孔用于定义多背景概念。对比度算子的目的在于对输入图像的灰度进行归一化,以避免不同区域之间的强度突然变化。最后,通过处理具有不同背景的图像来说明所提议的操作员的性能,其中大多数背景的照明条件较差。

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