基于小波稀疏的全息显微成像研究

The study of holographic microscopic imaging based on wavelet sparsity

数字全息显微镜要想满足高的分辨率通常需要获得许多张全息图,以达到较好的图像恢复效果。如果全息图的数量较少,则会导致重建的图像质量下降。由此提出一种基于小波稀疏重建的图像恢复方法,并对重建的图像用结构相似度指数来量化成像质量。通过获取人体血液红细胞的图像,得到3幅不同高度的全息图后进行稀疏重建,对这些图像进行结构相似性(SSIM)计算,其值为0.8407;再用4幅不同高度的全息图进行小波稀疏恢复,其SSIM值为0.8703。这种算法能够利用不同高度的少量全息图来重构生物样本的图像,比基于迭代多高度重建方法中使用的全息图的数量至少减少了两倍,并尽可能少地影响成像质量。同时,实现了无透镜超分辨的要求,且视野达到了20 mm2。基于小波稀疏的图像重构方法还可以应用于其他的成像方案中,例如用多个照明角度或波长来重构以增强相干成像的速度等方面。

Digital holographic microscopes usually need to obtain many holograms if they want to meet high resolution,in order to achieve better image restoration effects.If the number of holograms is reduced,the quality of the reconstructed image decreases.An image restoration method based on wavelet sparse reconstruction is proposed,and the structure similarity index is used to quantify the image quality of the reconstructed image.By acquiring images of human blood red blood cells,three holograms of different heights are obtained and then sparsely reconstructed,and the structural similarity(SSIM)calculation is performed on these images.The value is 0.8407.4 holograms of different heights are used for wavelet sparse recovery,and the SSIM value is 0.8703.This algorithm can use a small number of holograms of different heights to reconstruct the image of biological samples,which is at least twice the number of holograms used in the iterative multi-height reconstruction method,and affects the imaging quality as little as possible.At the same time,the requirement of lensless super-resolution was also realized,and the field of view reached 20 mm2.The image reconstruction method based on wavelet sparseness can also be applied to other imaging schemes,such as reconstructing with multiple illumination angles or wavelengths to enhance the speed of coherent imaging.