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Multilevel component-based histogram equalization for enhancing the quality of grayscale images

机译:基于多级分量的直方图均衡化,可增强灰度图像的质量

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Contrast enhancement is an important step in almost every image processing and computer vision application. Different applications demand different approaches to achieve the required level of enhancement. In consumer electronics, for example, any enhancement method should be able to enhance both global and local details but not at the expense of deterioration in image quality. In this paper we present our preliminary work on the development of a new method for image contrast enhancement called Multilevel Component-Based Histogram Equalization. This new method is simple and effective, and exploits the capabilities of the classical histogram equalization approach, multiple graylevel thresholding, and connected component analysis to allow for both global and local contrast enhancements with minimum distortion in image appearance. Visual and quantitative evaluation revealed the capability of the new method to achieve this goal.
机译:在几乎所有图像处理和计算机视觉应用中,对比度增强都是重要的一步。不同的应用程序需要不同的方法来达到所需的增强水平。例如,在消费类电子产品中,任何增强方法都应该能够增强全局和局部细节,但不能以降低图像质量为代价。在本文中,我们介绍了有关开发一种新的图像对比度增强方法的初步工作,该方法称为多级基于分量的直方图均衡。这种新方法既简单又有效,它利用了经典直方图均衡方法,多重灰度阈值和连接分量分析的功能,从而可以在图像外观失真最小的情况下增强全局和局部对比度。视觉和定量评估揭示了新方法实现此目标的能力。

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