基于欠曝光和过度曝光自适应划分的图像增强

Yanfang Wang, Qian Huang, Jing Hu
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引用次数: 1

摘要

在不均匀光照下拍摄的图像通常会因曝光不足和曝光过度而导致细节退化。为了提高彩色图像的视觉质量,欠曝需要调亮,过曝需要调暗。因此,在彩色图像中区分曝光不足和曝光过度是一个重要的步骤。传统方法在整个图像中使用一定的判别阈值。然而,在现实生活中,照明变化很容易发生。为了解决这一问题,我们提出了一种基于局部和全局亮度的自适应区分原则。然后,对图像亮度进行非线性修改,使曝光不足区域亮起来,过曝光区域变暗。在此基础上,利用修正后的亮度信息和原始色度信息,通过指数技术构建自然彩色图像。最后,在RGB通道中应用了一种局部和图像相关的指数技术来提高图像对比度。实验结果表明,该方法对非均匀光照图像和正常光照图像都能产生清晰生动的细节。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image enhancement based on adaptive demarcation between underexposure and overexposure
Images taken under non-uniform illumination usually suffer from degenerated details because of underexposure and overexposure. In order to improve the visual quality of color images, underexposure needs to be brightened and overexposure should be dimmed accordingly. Hence, an important procedure is discriminating between underexposure and overexposure in color images. Traditional methods utilize a certain discriminating threshold throughout an image. However, illumination variation occurs easily in real life. To cope with this, we propose an adaptive discriminating principle according to local and global luminance. Then, a nonlinear modification is applied to image luminance to light up underexposure and dim overexposure regions. Further, based on the modified luminance and original chromatic information, a natural color image is constructed via an exponential technique. Finally, a local and image-dependent exponential technique is applied to RGB channels to improve image contrast. Experimental results shows that the proposed method produces clear and vivid details for both non-uniform illumination images and images with normal illumination.
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