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Adaptive linear pixel-based fusion for contrast enhancement

机译:基于自适应的线性像素的对比度增强融合

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This paper presents an adaptive linear pixel-based fusion for contrast enhancement which is abbreviated as ALPS. The proposed ALPS approach combines the histogram equalization (HE) and image fusion schemes into one. A well-known problem in the HE is over-enhancement. It is also noted that a pixel-based fusion may suffer the problem of anomaly pixels. To avoid the problem of over-enhancement in the HE, an adaptive pixel-based fusion scheme is applied to the original image and its equalized image by the HE. Moreover, to deal with the problem of anomaly pixels, two restrictions are posed and a low-pass filter is used in the proposed ALPS approach. The simulation results indicate that the over-enhancement is relieved and that better enhanced images are for the proposed ALPS approach when compared with a HE-based contrast enhancement scheme. Also, the problem of anomaly pixels can be avoided by the proposed ALPS approach which is verified by the given examples, while the compared pixel-based fusion approach suffers it.
机译:本文介绍了一种基于自适应的线性像素的融合,用于对比度增强,缩写为阿尔卑斯山。所提出的ALPS方法将直方图均衡(HE)和图像融合方案组合成一个。他在他过度增强的众所周知的问题。还应注意,基于像素的融合可能遭受异常像素的问题。为了避免他在他的过度增强问题,基于自适应像素的融合方案被他应用于原始图像及其均衡图像。此外,为了处理异常像素的问题,提出了两个限制,并且在提出的ALP方法中使用了低通滤波器。仿真结果表明,与基于HE的对比度增强方案相比,仿真释放了过度增强且更好的增强图像用于提出的ALPS方法。而且,通过给定的实施例验证的所提出的ALP方法,可以避免异常像素的问题,而基于像素的融合方法则验证。

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