Edge detection based on gradient ghost imaging.
Edge detection based on gradient ghost imaging.
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DOI：
10.1364/oe.23.033802
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发表时间：
2015-12
期刊：
影响因子：
3.8
通讯作者：
Xue-feng Liu;Xu-Ri Yao;Ruo-ming Lan;Chao Wang;G. Zhai
中科院分区：
文献类型：
--
作者：
Xue-feng Liu;Xu-Ri Yao;Ruo-ming Lan;Chao Wang;G. Zhai
提出了一种基于GI的梯度域边缘检测的实验方法。通过对随机光场的修正，梯度GI(GGI)可以在不需要原始图像的情况下直接得到物体的边缘。由于实际物体的边缘通常比原始物体更稀疏，边缘检测结果的信噪比(SNR)将显著提高，特别是对于大面积、高透过率的物体。在本研究中，我们使用基于GI和GGI的双缝进行一维和二维边缘检测的实验。在这两种情况下，GGI的使用都显著提高了信噪比。对灰度级目标也进行了仿真研究。GI的独特优势使基于GGI的边缘检测在实际应用中具有一定的应用价值。
We present an experimental demonstration of edge detection based on ghost imaging (GI) in the gradient domain. Through modification of a random light field, gradient GI (GGI) can directly give the edge of an object without needing the original image. As edges of real objects are usually sparser than the original objects, the signal-to-noise ratio (SNR) of the edge detection result will be dramatically enhanced, especially for large-area, high-transmittance objects. In this study, we experimentally perform one- and two-dimensional edge detection with a double-slit based on GI and GGI. The use of GGI improves the SNR significantly in both cases. Gray-scale objects are also studied by the use of simulation. The special advantages of GI will make the edge detection based on GGI be valuable in real applications.