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The iterative detection network based suppression of the thermal noise and blurring due to object moving in black and white pictures shot by a camera with CCD/CMOS sensor

机译:基于迭代检测网络的热噪声和模糊的抑制,该噪声是由带有CCD / CMOS传感器的相机拍摄的黑白照片中的物体移动引起的

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The paper deals with elimination of blurring caused by the object moving and thermal noise in black & white pictures captured by a CCD/CMOS camera. This problem can be also interpreted like image passage through some kind of ISI channel with specific 2D impulse response. Hence for purposes of image recovery we can use the MAP criterion based iterative detection network (IDN) containing a number of mutually concatenated functional blocks so-called soft inversions (SISOs). This cellular structure makes IDN suboptimal but also numerically very simple and practically applicable in contrast to an unviable optimal (single-stage) MAP detector. Firstly we focus closer to parameters determination of the image blurring hypothetical model (misrepresenting ISI channel). Consequently we are going to deal with the SISO entities and the synthesis of entire IDN, specifically the synthesis of so-called distributed IDN marginalizing at the symbol level because this structure presents the best solution for the mentioned issue. At the end, the image reconstruction example will be presented (using this type of IDN).
机译:本文致力于消除由CCD / CMOS相机拍摄的黑白图像中的物体移动和热噪声引起的模糊。这个问题也可以像具有特定2D脉冲响应的图像通过某种ISI通道一样来解释。因此,出于图像恢复的目的,我们可以使用基于MAP准则的迭代检测网络(IDN),其中包含许多相互串联的功能块,即所谓的软反转(SISO)。与不可行的最佳(单级)MAP检测器相比,这种细胞结构使IDN次优,但在数值上也非常简单且在实践中适用。首先,我们将注意力集中在图像模糊假设模型的参数确定上(表示ISI通道不正确)。因此,我们将要处理SISO实体以及整个IDN的综合,特别是在符号级别上边缘化所谓的分布式IDN的综合,因为这种结构为上述问题提供了最佳解决方案。最后,将展示图像重建示例(使用这种类型的IDN)。

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