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Content-Preserving Tone Adjustment for Image Enhancement

机译:图像增强的内容保留音调调整

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We propose a novel method based on Convolutional Neural Networks for content-preserving tone adjustment. The method is at the same time fast and accurate since we decouple the inference of the parameters and the color transform: the parameters are inferred from a downsampled version of the input image and the transformation is applied to the full resolution input. The method includes two steps of image enhancement: the first one is a global color transformation, while the second one is a local transformation. Experiments conducted on the DPED - DSLR Photo Enhancement Dataset, that has been used for the NTIRE19 Image Enhancement Challenge, and on the MIT-Adobe FiveK dataset, that is widely used for image enhancement, demonstrate the effectiveness of the proposed method.
机译:我们提出了一种基于卷积神经网络的新方法,用于保持内容保留音调调整。该方法同时快速准确,因为我们将参数的推断和颜色变换分离:从输入图像的下采样版本推断参数,并将变换应用于全分辨率输入。该方法包括两个图像增强步骤:第一个是全局颜色变换,而第二个是局部变换。在DPED-DSLR照片增强数据集上进行的实验,该数据集已用于NTIRE19图像增强挑战,并且在MIT-Adobe 5K数据集上广泛用于图像增强,证明了所提出的方法的有效性。

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