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CCD Noise Removal in Digital Images

机译:数字图像中的CCD噪声消除

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In this work, we propose a denoising scheme to restore images degraded by CCD noise. The CCD noise model, measured in the space of incident light values (light space), is a combination of signal-independent and signal-dependent noise terms. This model becomes more complex in image brightness space (normal camera output) due to the nonlinearity of the camera response function that transforms incoming data from light space to image space. We develop two adaptive restoration techniques, both accounting for this nonlinearity. One operates in light space, where the relationship between the incident light and light space values is linear, while the second method uses the transformed noise model to operate in image space. Both techniques apply multiple adaptive filters and merge their outputs to give the final restored image. Experimental results suggest that light space denoising is more efficient, since it enables the design of a simpler filter implementation. Results are given for real images with synthetic noise added, and for images with real noise.
机译:在这项工作中,我们提出了一种去噪方案来恢复由于CCD噪声而退化的图像。在入射光值空间(光空间)中测量的CCD噪声模型是独立于信号和独立于信号的噪声项的组合。由于相机响应函数的非线性(将传入数据从光空间转换到图像空间),该模型在图像亮度空间(正常相机输出)中变得更加复杂。我们开发了两种自适应恢复技术,都解决了这种非线性问题。一种是在光空间中操作,其中入射光和光空间值之间的关系是线性的,而第二种方法是使用变换后的噪声模型在图像空间中进行操作。两种技术都应用多个自适应滤波器并合并其输出以提供最终的还原图像。实验结果表明,光空间降噪更有效,因为它可以设计更简单的滤波器实现。给出了添加了合成噪声的真实图像和具有真实噪声的图像的结果。

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