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Image Decomposition Based Nighttime Image Enhancement

机译:基于图像分解的夜间图像增强

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Nighttime image captured at low or non-uniform illumination scene always suffers from the loss of visibility, and contains various noise and objectionable artifact. When we enlarge the amplitude of the lightness, the noise and artifact in nighttime images will be amplified. Hence, we propose a nighttime image enhancement method based on image decomposition. We decompose the input image into two components: Structure Layer contains main information of the image, and Texture Layer contains details, noise and artifact. For the Structure Layer, we apply an improved-Retinex image enhancement algorithm. To remain details and suppress noise and artifact in the Texture Layer, we use Mask Weighted Least Squares method. In the final, we fuse these two components to get the result. The experimental results demonstrate that the proposed approach can improve the perceptual quality of night-time image while suppressing noise and artifact, and avoiding excessive reinforcement.
机译:在低或非均匀照明场景中捕获的夜间图像总是遭受可见性的损失,并包含各种噪声和令人讨厌的伪影。当我们扩大亮度的幅度时,将放大夜间图像中的噪声和伪影。因此,我们提出了一种基于图像分解的夜间图像增强方法。我们将输入图像分解为两个组件:结构层包含图像的主要信息,纹理层包含细节,噪声和伪像。对于结构层,我们应用改进的Retinex图像增强算法。为了保持细节和抑制纹理层中的噪声和伪影,我们使用屏蔽加权最小二乘法方法。在决赛中,我们融合了这两个组件以获得结果。实验结果表明,该方法可以提高夜间图像的感知质量,同时抑制噪声和伪影,避免过度加固。

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