Progressive-CRF-net: single image radiometric calibration using stacked CNNs

Yi-Lung Kao, Yu-Sheng Chen, M. Ouhyoung
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引用次数: 2

Abstract

A camera is a good instrument for measuring scene radiance. However, to please the human eye, the resulting image brightness is not linear to the scene radiance, so solving the mapping function between scene radiance and image brightness is very important. We propose a Progressive-CRF-net for radiometric calibration. By stacking multiple networks and using the pre-trained weights, this approach can reduce the training time and reach better performance than that of previous work. Our experiments show a significant improvement based on PSNR and SSIM.
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渐进式crf网络:使用堆叠cnn的单图像辐射定标
相机是测量场景亮度的好工具。然而,为了取悦人眼,得到的图像亮度与场景亮度不是线性的,因此解决场景亮度与图像亮度之间的映射函数是非常重要的。我们提出了一种渐进式crf网用于辐射校准。该方法通过对多个网络进行叠加,并使用预先训练好的权值,减少了训练时间,达到了比以往工作更好的性能。我们的实验表明,在PSNR和SSIM的基础上有了明显的改进。
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