CCD noise removal in digital images
CCD noise removal in digital images
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DOI：
10.1109/tip.2006.877363
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发表时间：
2006-09-01
影响因子：
10.6
通讯作者：
MacLean, W. James
中科院分区：
文献类型：
--
作者：
Faraji, Hilda;MacLean, W. James
在这项工作中，我们提出了一个去噪方案来恢复图像退化的CCD噪声。在入射光值的空间（光空间）中测量的CCD噪声模型是信号无关噪声项和信号相关噪声项的组合。由于相机响应函数的非线性，该模型在图像亮度空间（正常相机输出）中变得更加复杂，该相机响应函数将输入数据从光空间转换为。图像空间我们开发了两种自适应恢复技术，都占这种非线性。第一种方法在光空间中操作，其中入射光和光空间值之间的关系是线性的，而第二种方法使用变换的噪声模型在图像空间中操作。这两种技术都应用多个自适应滤波器并合并它们的输出以给出最终的恢复图像。实验结果表明，光空间去噪更有效，因为它可以设计更简单的滤波器实现。结果给出了真实的图像与合成噪声添加，并与真实的噪声的图像。
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.