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Image enhancement based on adaptive demarcation between underexposure and overexposure

机译:基于曝光不足和曝光过度之间自适应分界的图像增强

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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.
机译:由于曝光不足和曝光过度,在不均匀照明下拍摄的图像通常会出现退化的细节。为了改善彩色图像的视觉质量,需要调亮曝光不足,并相应地调低曝光过度。因此,重要的步骤是区分彩色图像的曝光不足和曝光过度。传统方法在整个图像中利用特定的区分阈值。但是,在现实生活中容易发生照明变化。为了解决这个问题,我们提出了一种根据局部和全局亮度的自适应判别原理。然后,将非线性修改应用于图像亮度以照亮曝光不足和暗淡的过度曝光区域。此外,基于修改后的亮度和原始色度信息,通过指数技术构造自然彩色图像。最后,将局部和图像相关的指数技术应用于RGB通道,以提高图像对比度。实验结果表明,该方法对于不均匀的照明图像和正常照明的图像都能产生清晰生动的细节。

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