基于BBHE和BPHEME混合直方图均衡化方法的弱光图像对比度增强

Sudeep D. Thepade, Mallikarjun Ople, Vaibhav Mahindra, Vrushabh Kulye, Sudarshan Jamdar
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引用次数: 2

摘要

图像对比度是图像的一部分与周围物体的亮度和颜色之间的差异。对比度增强是指增加原始输入亮度值。在低光环境中拍摄的图像由于对比度低而能见度较低。直方图均衡化是图像对比度增强的基础,甚至被用于新的对比度增强方法中。尽管直方图均衡化(HE)是原始的,但它是有效的。HE显著地增加了输出图像的亮度,这通常是不希望看到的。人们提出了各种增强的直方图均衡化方法来提高图像对比度,以克服亮度保持和图像细节保持的挑战。本文重点研究了基于图像、PSNR -峰值信噪比、BRISQUE -盲/无参考图像空间质量评价器和熵的不同流行和认可的HE方法和实验研究。上述研究结果将目标指向了所选择的两种方法的图像融合,在原始图像的亮度保持和对比度增强方面取得了较好的效果。
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Low Light Image Contrast Enhancement using Blending of Histogram Equalization Based Methods BBHE and BPHEME
Image contrast is the difference between the brightness and colors of a part of an image compared to its objects around. The contrast enhancement means increasing the original input brightness values. Images captured in low-light environments suffer from inferior visibility caused by low contrast. It is said that Histogram equalization is the foundation of image contrast enhancement and is used even in new contrast enhancement methods. Even though Histogram Equalization (HE) is primitive, it is effective. HE increases the brightness of the output image significantly, which is often undesirable. There are various enhanced versions of histogram equalization methods to improve image contrast are proposed to overcome the brightness preservation and image details preservation challenge. This paper focuses on studying different popular and approved HE methods and experimental studies based on the image, PSNR - peak signal to noise ratio, BRISQUE - Blind / Reference less Image Spatial Quality Evaluator, and Entropy. Results from the above study direct the goal towards the Image fusion of the two selected methods, which gives improved results on the preservation of brightness and contrast enhancement of the original image.
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