鬼影成像
图像质量
降噪
散斑噪声
光学
斑点图案
噪音(视频)
迭代法
计算机科学
迭代和增量开发
迭代重建
人工智能
图像处理
计算机视觉
图像(数学)
算法
物理
软件工程
作者
Xu‐Ri Yao,Wen-Kai Yu,Xue-Feng Liu,Longzhen Li,Mingfei Li,Ling-An Wu,Guang-Jie Zhai
出处
期刊:Optics Express
[Optica Publishing Group]
日期:2014-09-25
卷期号:22 (20): 24268-24268
被引量:56
摘要
We present a new technique to denoise ghost imaging (GI) in which conventional intensity correlation GI and an iteration process have been combined to give an accurate estimate of the actual noise affecting image quality. The blurring influence of the speckle areas in the beam is reduced in the iteration by setting a threshold. It is shown that with an appropriate choice of threshold value, the quality of the iterative GI reconstructed image is much better than that of differential GI for the same number of measurements. This denoising method thus offers a very effective approach to promote the implementation of GI in real applications.
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