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Vector Color Filter Array Demosaicing

机译:矢量滤色器阵列脱模

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摘要

Single-sensor digital cameras spatially sample the incoming image using a color filter array (CFA). Consequently, each pixel only contains a single color value. In order to reconstruct the original full-color image, a demosaicing step must be performed which interpolates the missing colors at each pixel. Goals in CFA demosaicing include color fidelity, spatial resolution, no false colors, no jagged edges, and computational practicality. Most demosaicing algorithms do well for color fidelity, but there is often a trade-off between a sharp image and the so-called "zipper effect" or jagged edge look. We propose a novel demosaicing algorithm called Vector Demosaicing that interpolates missing colors jointly by selecting the color vector that minimizes the sum of distances to the surrounding pixels. The selected color vector is a vector median of the surrounding pixels. The vector median forms an "average", but preserves sharp edges. We will discuss the theory behind our approach and show experimentally how the theoretical advantages manifest themselves to improve edge resolution while retaining smoothness. Computational complexity is shown to be possibly quite low, and we discuss how different approximations may affect the output.
机译:单传感器数码相机使用滤色器阵列(CFA)在空间上抽样。因此,每个像素仅包含单个颜色值。为了重建原始的全彩色图像,必须执行去解析步骤,其在每个像素处插入缺失的颜色。 CFA Demosaicing的目标包括颜色保真度,空间分辨率,没有假颜色,没有锯齿状的边缘和计算实用性。大多数去脱糖算法对于颜色保真度进行良好,但在锐利的图像和所谓的“拉链效果”或锯齿状边缘时通常会有权衡。我们提出一种名为载体去染料的新型去染算法,其通过选择最小化到周围像素的距离和的彩色载体来插入缺失颜色。所选择的彩色载体是周围像素的矢量中位数。载体中位数形成“平均”,但保留锋利的边缘。我们将讨论我们的方法背后的理论,并通过实验表明理论优势如何表明自己在保持平滑度的同时提高边缘分辨率。计算复杂性显示可能相当低,我们讨论了不同的近似值如何影响输出。

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