摘要
针对数字全息图像背景去除的问题,提出两种全息图像重建去背景的方法:背景减弱法和自适应滤波法.搭建了共轴数字全息显微成像实验系统,利用该系统分别对洋葱表皮、植物根茎横切标本、叶片气孔标本和血细胞标本进行背景去除和图像重建.通过光强分布曲线、对比度计算等证明了自适应滤波方法在共轴数字全息结构中去除背景的有效性.实验结果表明,根据环境、样品等不同,全息图的背景也会发生变化.基于此结果,将全息数字显微图像分为三类,并针对不同的背景特点,得出了获取最佳重建图像应采用的有效去除背景方法.研究结果有助于共轴光路数字全息显微术中的重建成像.
Background decrease method and adaptive filtering methods were proposed to solve the background removing problem in digital holographic microscopy in the in-line digital holographic microscopy. In-line digital holography microscopic system was set up, with which the digital holographic images of onion epidermis, the plant roots' sample, the lamina stoma sample and the blood cell sample were reconstructed, respectively. In addition, the advantages of the proposed methods were demonstrated by calculating the light intensity distribution curves and the values of the contrast of images obtained with the in-line digital holographic microscope device. The results show that the backgrounds in the measured holographic interferometric fringes change with the experimental conditions and the sample itself. So that the backgrounds could be divided into three types, for each of which an appropriate method was proposed to achieve the best reconstruction image quality. The results may be helpful for reconstructing the better quality images.
出处
《光子学报》
EI
CAS
CSCD
北大核心
2015年第3期63-69,共7页
Acta Photonica Sinica
基金
国家自然科学基金(Nos.61275198
60978069)
国防基础科研项目资助
关键词
数字全息
共轴全息
自适应滤波
背景减弱
全息图像
去除零级
背景分类
Digital holography
In-line holographic microscopy
Adaptive filtering
Background decrease
Holographic image
Removing zero-order
Classification of background