Joint demosaicing and denoising
Joint demosaicing and denoising
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DOI：
10.1109/icip.2005.1530390
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发表时间：
2006-08
影响因子：
10.6
通讯作者：
Keigo Hirakawa;T. Parks
中科院分区：
文献类型：
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作者：
Keigo Hirakawa;T. Parks
由于图像传感器中的噪声，数码相机的输出图像受到严重的劣化。本文提出了一种新的技术，联合收割机去马赛克和去噪程序系统地到一个单一的操作，利用他们明显的相似性。我们首先设计一个滤波器，就好像我们是从一个嘈杂的单色（传感器）图像中最佳地估计像素值。有了额外的限制，我们表明，相同的滤波器系数是适当的彩色滤光片阵列插值（去马赛克）噪声传感器数据。所提出的技术可以将联合收割机许多现有的去噪算法与去马赛克操作相结合。在本文中，总体最小二乘去噪方法被用来证明的概念。该算法进行了测试的彩色图像与伪随机噪声和原始传感器数据从一个真实的CMOS数码相机，我们校准。实验结果证实，该方法抑制噪声（CMOS/CCD图像传感器噪声模型），同时有效地内插丢失的像素分量，表现出显着改善图像质量相比，单独处理去马赛克和去噪问题
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