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Revertible Guidance Image Based Image Detail Enhancement

机译:基于可替代的引导图像的图像细节增强

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Image detail enhancement is widely used in image processing tasks to give better look and higher contrast to images and photos. However, the reverse process that converts an enhanced image back to its original image usually does not have an explicit representation given only the enhanced image is available. In this work, we propose a generic framework of revertible image detail enhancement so that we can estimate the original image without extra information. We define a family of revertible detail enhancement operators that convert each pixel from original image to enhanced image and vice versa. A guidance image is used to decide which operator to use for each pixel. In the enhancement process, the guidance image is generated from the original image. In the reverse process, the guidance image is estimated from iterative optimization, making the process revertible. Experimental results show that the proposed enhancement framework can convert the enhanced image back to its original image without noticeable difference.
机译:图像细节增强广泛用于图像处理任务,以提供更好的外观和更高的图像和照片对比度。然而,将增强型图像转换回其原始图像的反向过程通常没有给出增强图像可用的显式表示。在这项工作中,我们提出了一种可替代图像细节增强的通用框架,以便在没有额外信息的情况下估计原始图像。我们定义了一系列可替代的细节增强算子,可将每个像素从原始图像转换为增强的图像,反之亦然。指导图像用于确定用于每个像素的操作员。在增强过程中,从原始图像生成引导图像。在反向过程中,引导图像估计从迭代优化,使得过程可重复。实验结果表明,所提升框架可以将增强型图像转换回其原始图像而不明显差异。

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