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基于频域的彩色滤波器阵列自动设计

Automatic Design of Color Filter Arrays in the Frequency Domain.

出版信息

IEEE Trans Image Process. 2016 Apr;25(4):1793-807. doi: 10.1109/TIP.2016.2531287. Epub 2016 Feb 18.

Abstract

In digital color imaging, the raw image is typically obtained through a single sensor covered by a color filter array (CFA), which allows only one color component to be measured at each pixel. The procedure to reconstruct a full color image from the raw image is known as demosaicking. Since the CFA may cause irreversible visual artifacts, the CFA and the demosaicking algorithm are crucial to the quality of demosaicked images. Fortunately, the design of CFAs in the frequency domain provides a theoretical approach to handling this issue. However, almost all the existing design methods in the frequency domain involve considerable human effort. In this paper, we present a new method to automatically design CFAs in the frequency domain. Our method is based on the frequency structure representation of mosaicked images. We utilize a multi-objective optimization approach to propose frequency structure candidates, in which the overlap among the frequency components of images mosaicked with the CFA is minimized. Then, we optimize parameters for each candidate, which is formulated as a constrained optimization problem. We use the alternating direction method to solve it. Our parameter optimization method is applicable to arbitrary frequency structures, including those with conjugate replicas of chrominance components. Experiments on benchmark images confirm the advantage of the proposed method.

摘要

在数字彩色成像中,原始图像通常是通过一个覆盖有彩色滤波器阵列 (CFA) 的单个传感器获得的,该传感器允许在每个像素处仅测量一个颜色分量。从原始图像重建全彩色图像的过程称为去马赛克。由于 CFA 可能会导致不可逆转的视觉伪影,因此 CFA 和去马赛克算法对于去马赛克图像的质量至关重要。幸运的是,CFA 在频域的设计为解决这个问题提供了一种理论方法。然而,几乎所有现有的频域设计方法都需要大量的人工努力。在本文中,我们提出了一种在频域中自动设计 CFA 的新方法。我们的方法基于马赛克图像的频域结构表示。我们利用多目标优化方法来提出频域结构候选者,其中 CFA 马赛克化的图像的频率分量之间的重叠最小。然后,我们为每个候选者优化参数,这被表述为一个约束优化问题。我们使用交替方向法来解决它。我们的参数优化方法适用于任意的频域结构,包括具有颜色分量共轭副本的结构。基准图像上的实验证实了所提出方法的优势。

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