Low-Light Image Deblurring Based on Simple Lens System

Dazhi Zhan, Xiangrong Zeng, Weili Li, Yu Liu, Z. Xiong
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Abstract

A method for image quality enhancement of simple lens image under low-illumination condition is presented in this paper. We first introduce an accurate camera-scene alignment framework that generates exactly matched and tone-consistent image pairs to estimate blur kernel. We then use the cross-channel matrix obtained in the tone curve calibration to restore the details of the blurred image. Finally, the clear image is restored by non-blind deconvolution and compared with other methods to prove the advantages of our method.
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基于简单透镜系统的微光图像去模糊
提出了一种在低照度条件下提高简单透镜图像质量的方法。我们首先引入了一个精确的相机场景对齐框架,生成精确匹配和色调一致的图像对来估计模糊核。然后,我们使用色调曲线校准中获得的跨通道矩阵来恢复模糊图像的细节。最后,通过非盲反卷积恢复清晰图像,并与其他方法进行比较,证明了本文方法的优越性。
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