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Joint demosaicing and denoising

机译:联合去马赛克和去噪

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The output image of a digital camera is subject to a severe degradation due to noise in the image sensor. This paper proposes a novel technique to combine demosaicing and denoising procedures systematically into a single operation by exploiting their obvious similarities. We first design a filter as if we are optimally estimating a pixel value from a noisy single-color (sensor) image. With additional constraints, we show that the same filter coefficients are appropriate for color filter array interpolation (demosaicing) given noisy sensor data. The proposed technique can combine many existing denoising algorithms with the demosaicing operation. In this paper, a total least squares denoising method is used to demonstrate the concept. The algorithm is tested on color images with pseudorandom noise and on raw sensor data from a real CMOS digital camera that we calibrated. The experimental results confirm that the proposed method suppresses noise (CMOS/CCD image sensor noise model) while effectively interpolating the missing pixel components, demonstrating a significant improvement in image quality when compared to treating demosaicing and denoising problems independently.
机译:由于图像传感器中的噪声,数码相机的输出图像会严重劣化。本文提出了一种新颖的技术,通过利用它们的明显相似性,将去马赛克和去噪过程系统地组合到单个操作中。我们首先设计一个滤波器,就好像我们是从嘈杂的单色(传感器)图像中最佳估计像素值一样。在附加的约束条件下,我们表明在给定嘈杂的传感器数据的情况下,相同的滤波器系数适用于彩色滤光片阵列插值(去马赛克)。所提出的技术可以将许多现有的去噪算法与去马赛克操作相结合。在本文中,使用总最小二乘法去噪方法来证明这一概念。该算法在带有伪随机噪声的彩色图像上以及在我们校准过的真实CMOS数码相机的原始传感器数据上进行了测试。实验结果证实,与独立处理去马赛克和去噪问题相比,该方法在有效地内插缺失像素分量的同时,抑制了噪声(CMOS / CCD图像传感器噪声模型),显示出图像质量的显着改善。

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