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Adaptive enhancement for nonuniform illumination images via nonlinear mapping

机译:通过非线性映射对非均匀照明图像进行自适应增强

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Nonuniform illumination images suffer from degenerated details because of underexposure, overexposure, or a combination of both. To improve the visual quality of color images, underexposure regions should be lightened, whereas overexposure areas need to be dimmed properly. However, discriminating between underexposure and overexposure is troublesome. Compared with traditional methods that produce a fixed demarcation value throughout an image, the proposed demarcation changes as local luminance varies, thus is suitable for manipulating complicated illumination. Based on this locally adaptive demarcation, a nonlinear modification is applied to image luminance. Further, with the modified luminance, we propose a nonlinear process to reconstruct a luminance-enhanced color image. For every pixel, this nonlinear process takes the luminance change and the original chromaticity into account, thus trying to avoid exaggerated colors at dark areas and depressed colors at highly bright regions. Finally, to improve image contrast, a local and image-dependent exponential technique is designed and applied to the RGB channels of the obtained color image. Experimental results demonstrate that our method produces good contrast and vivid color for both nonuniform illumination images and images with normal illumination. (C) The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.
机译:由于曝光不足,曝光过度或两者结合,导致不均匀的照明图像细节退化。为了提高彩色图像的视觉质量,应将曝光不足的区域变亮,而过度曝光的区域则需要适当调暗。但是,区分曝光不足和曝光过度很麻烦。与在整个图像中产生固定分界值的传统方法相比,建议的分界随着局部亮度的变化而变化,因此适合于操纵复杂的照明。基于此局部自适应分界,将非线性修改应用于图像亮度。此外,利用修改后的亮度,我们提出了一种非线性过程来重建亮度增强的彩色图像。对于每个像素,此非线性过程都将亮度变化和原始色度考虑在内,因此尝试避免在深色区域使用夸张的颜色,而在高亮度区域使用避免压抑的颜色。最后,为了提高图像对比度,设计了一种局部的,依赖于图像的指数技术,并将其应用于获得的彩色图像的RGB通道。实验结果表明,我们的方法对于不均匀的照明图像和正常照明的图像都能产生良好的对比度和鲜艳的色彩。 (C)作者。由SPIE根据Creative Commons Attribution 3.0 Unported License发布。分发或复制此作品的全部或部分,需要对原始出版物(包括其DOI)进行完全归因。

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