基于混合散斑图的压缩计算鬼成像方法研究  

Hybrid Speckle-Pattern Compressive Computational Ghost Imaging

作　　者：周成[1,2,3] 黄贺艳 刘兵[1,2] 宋立军[1,2] 

机构地区：[1]长春大学理学院,吉林长春130022 [2]长春大学材料设计与量子模拟吉林省高校重点实验室,吉林长春130022 [3]长春理工大学理学院,吉林长春130022

出　　处：《光学学报》2016年第9期91-97,共7页Acta Optica Sinica

基　　金：国家自然科学基金(11347013);吉林省科技发展计划项目(20130521016JH;20140101187JC);长春市科技发展计划项目(2014217)

摘　　要：提出一种基于混合散斑图的压缩计算鬼成像方法。通过对不同分辨率尺度组成的复杂物体进行自动识别,检测出物体中较大和较小分辨率区域,根据识别区域生成由不同大小尺寸散斑组成的混合散斑图进行探测,结合压缩感知对恢复图像进行处理。通过理论分析和数值仿真发现,与传统计算鬼成像方法相比,该方法克服了散斑大小选取不适当对恢复图像质量的影响,显著提高了恢复图像的衬噪比和可见度,有效降低了均方误差。该方法在提高成像质量的同时减少采样时间,有利于进一步推动计算鬼成像技术的实用化。A method of the hybrid speckle-pattern compressive computational ghost imaging scheme is proposed. The scheme detects the larger and smaller resolution areas of the object via identifying complex object composed of different resolution scales automatically. The hybrid speckle pattern composed of different sizes of speckles is generated according to the identify areas. The compressive sensing techniques are combined to process the reconstructed image. Theoretical analysis and numerical simulation show that compared with the traditional computational ghost imaging, this scheme overcomes the influence of inappropriate selection of speckle sizes on the quality of reconstructed image, enhances the image contrast-to-noise ratio and visibility significantly, mean square error effectively. The scheme improves the image quality while reducing the sampling time, which further facilitate the practical application of computational ghost imaging.

关 键 词：成像系统 计算鬼成像 压缩感知 混合散斑图 衬噪比 均方误差 

分 类 号：O438[机械工程—光学工程]