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McCann's Retinex Enhancement Method Based on YUV for Space Station Image

机译:基于YUV的空间站图像的McCann的retinex增强方法

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In the space station, the hash and uneven illumination brings a significant challenge to the vision system, which is the precondition of monitoring, unattended operation and robot operation. This challenge is caused by the high dynamic range of light intensity and the light reflection of metal facilities. Aiming at this problem, Retinex algorithm was proposed to estimate the luminosity. Firstly, the structure and mechanism of human eyes are analyzed. Secondly, based on that, McCann's Retinex algorithm is used to enhanced the images. Finally, the original image is enhanced by merging the new brightness layer and the color layer. The experimental results show the validity of the proposed algorithm.
机译:在空间站,散列和不均匀的照明对视觉系统带来了重大挑战,这是监控,无人看管的操作和机器人操作的前提。这种挑战是由金属设施的高动态范围和光反射引起的。针对这个问题,提出了retinex算法来估计亮度。首先,分析了人眼的结构和机制。其次,基于此,McCann的RetineX算法用于增强图像。最后,通过合并新的亮度层和颜色层来增强原始图像。实验结果表明了该算法的有效性。

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