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首页> 外文期刊>IEICE Transactions on Information and Systems >Noise Reduction Method for Image Signal Processor Based on Unified Image Sensor Noise Model
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Noise Reduction Method for Image Signal Processor Based on Unified Image Sensor Noise Model

机译：基于统一图像传感器噪声模型的图像信号处理器降噪方法

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摘要

The noise in digital images acquired by image sensors has complex characteristics due to the variety of noise sources. However, most noise reduction methods assume that an image has additive white Gaussian noise (AWGN) with a constant standard deviation, and thus such methods are not effective for use with image signal processors (ISPs). To efficiently reduce the noise in an ISP, we estimate a unified noise model for an image sensor that can handle shot noise, dark-current noise, and fixed-pattern noise (FPN) together, and then we adaptively reduce the image noise using an adaptive Smallest Univalue Segment Assimilating Nucleus (SUSAN) filter based on the unified noise model. Since our noise model is affected only by image sensor gain, the parameters for our noise model do not need to be re-configured depending on the contents of image. Therefore, the proposed noise model is suitable for use in an ISP. Our experimental results indicate that the proposed method reduces image sensor noise efficiently.
机译：由于噪声源的多样性，图像传感器获取的数字图像中的噪声具有复杂的特性。但是，大多数降噪方法都假定图像具有标准偏差恒定的加性高斯白噪声（AWGN），因此，此类方法不适用于图像信号处理器（ISP）。为了有效降低ISP中的噪声，我们为图像传感器估计了一个统一的噪声模型，该模型可以同时处理散粒噪声，暗电流噪声和固定模式噪声（FPN），然后使用基于统一噪声模型的自适应最小单值分段同化核（SUSAN）滤波器。由于我们的噪声模型仅受图像传感器增益的影响，因此无需根据图像内容重新配置噪声模型的参数。因此，建议的噪声模型适合在ISP中使用。我们的实验结果表明，该方法可以有效降低图像传感器的噪声。

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