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首页> 外文期刊>Image Processing, IET >Cross-channel regularisation for joint demosaicking and intrinsic lens deblurring
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Cross-channel regularisation for joint demosaicking and intrinsic lens deblurring

机译：跨通道正则化，用于联合去马赛克和固有镜片去模糊

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Here, the authors present an effective regularisation approach to colour image demosaicking. The authors' work is inspired by the interesting observation that the cross-channel dependencies of high-frequency details of a colour image are supposed to correspond in all the main colour channels acquired by the sensor. Therefore, minimising their difference in the demosaicking process can significantly improve the quality of the reconstructed image. The authors also demonstrate that mosaicked image formation strictly depends on the intrinsic lens blur. Hence, in the authors' solution to the image demosaicking as an inverse imaging problem, they take the lens blur characteristics into account. The proposed regularisation method is also based on the fact that sensor saturation significantly alters the distribution of pixel intensity and Gaussian noise. The authors develop an efficient solution to the problem via the alternating direction method of multipliers numerical solver. As a result of these steps, the proposed demosaicking approach significantly enhances the quality of reconstructed images. Experimental results and quantitative evaluations demonstrate that the proposed method outperforms the existing image demosaicking methods.
机译：在这里，作者提出了一种有效的正则化方法来进行彩色图像去马赛克。作者的工作受到有趣的观察的启发，该观察认为，彩色图像高频细节的跨通道依赖性在传感器获取的所有主要彩色通道中都应对应。因此，最小化它们在去马赛克过程中的差异可以显着提高重建图像的质量。作者还证明，镶嵌图像的形成严格取决于镜片固有的模糊。因此，在作者将图像去马赛克作为逆成像问题的解决方案中，他们考虑了镜头模糊特性。所提出的正则化方法还基于以下事实：传感器饱和会显着改变像素强度和高斯噪声的分布。作者通过乘数值解算器的交替方向方法开发了一种有效的解决方案。这些步骤的结果是，提出的去马赛克方法大大提高了重建图像的质量。实验结果和定量评估表明，该方法优于现有的图像去马赛克方法。

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