全息术
计算机视觉
计算机科学
人工智能
光学(聚焦)
光学
噪音(视频)
霍夫变换
迭代重建
物理
图像(数学)
作者
Yiyi zhang,Zhengzhong Huang,Shangzhong Jin,Liangcai Cao
出处
期刊:Applied Optics
[The Optical Society]
日期:2023-01-11
卷期号:62 (10): D23-D23
被引量:2
摘要
Reconstruction of multiple objects from one hologram can be affected by the focus metric judgment of autofocusing. Various segmentation algorithms are applied to obtain a single object in the hologram. Each object is unambiguously reconstructed to acquire its focal position, which produces complicated calculations. Herein, Hough transform (HT)-based multi-object autofocusing compressive holography is presented. The sharpness of each reconstructed image is computed by using a focus metric such as entropy or variance. According to the characteristics of the object, the standard HT is further used for calibration to remove redundant extreme points. The compressive holographic imaging framework with a filter layer can eliminate the inherent noise in in-line reconstruction including cross talk noise of different depth layers, two-order noise, and twin image noise. The proposed method can effectively obtain 3D information on multiple objects and achieve noise elimination by only reconstructing from one hologram.
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