基于迭代检测网络的相机黑白图像恢复(实现与降复杂度问题)

D. Kekrt, M. Klima
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引用次数: 4

摘要

本文研究了非完全调整镜头的CCD (CMOS)相机拍摄的黑白图像的散焦和泊松(镜头)噪声消除问题。为了这种图像恢复的目的,我们可以使用基于MAP准则的迭代检测网络(IDN),该网络包含许多相互连接的基本功能块,即所谓的软反转(SISOs)。这种细胞结构使得IDN不是最优的,但与不可行的最优(单级)MAP检测器相比,它在数值上非常简单,并且实际适用。首先,我们更密切地关注SISO实体,从而关注整个IDN的创建。本文将介绍两种不同形式的重建系统(分布式IDN),以及其中一种形式的图像重建的复杂性降低可能性和示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The iterative detection network based recovery of black & white pictures shot by camera (implementation and complexity reduction issue)
The paper deals with a defocusing and Poisson (shot) noise elimination out of black & white pictures captured by a CCD (CMOS) camera with imperfectly adjusted lens. For purposes of this image recovery we can use the MAP criterion based iterative detection network (IDN) containing a number of mutually concatenated elementary function blocks so-called soft inversions (SISOs). This cellular structure makes IDN suboptimal but also numerically very simple and practically applicable in contrast to unviable optimal (single-stage) MAP detector. Firstly we focus closer on SISO entities and consequently on the creation of entire IDN. There will be introduced two different forms of reconstruction system (distributed IDN) together with complexity reduction possibilities and example of the image reconstruction by one of them.
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