Blind restoration method of three-dimensional microscope image based on RL algorithm

Jin-li Yao; Si Tian; Xiang-rong Wang; Jing-li Wang

doi:10.1117/12.2034965

20 August 2013 Blind restoration method of three-dimensional microscope image based on RL algorithm

Jin-li Yao, Si Tian, Xiang-rong Wang, Jing-li Wang

Proceedings Volume 8913, International Symposium on Photoelectronic Detection and Imaging 2013: Optical Storage and Display Technology; 89130Z (2013) https://doi.org/10.1117/12.2034965
Event: ISPDI 2013 - Fifth International Symposium on Photoelectronic Detection and Imaging, 2013, Beijing, China

Abstract

Thin specimens of biological tissue appear three dimensional transparent under a microscope. The optic slice images can be captured by moving the focal planes at the different locations of the specimen. The captured image has low resolution due to the influence of the out-of-focus information comes from the planes adjacent to the local plane. Using traditional methods can remove the blur in the images at a certain degree, but it needs to know the point spread function (PSF) of the imaging system accurately. The accuracy degree of PSF influences the restoration result greatly. In fact, it is difficult to obtain the accurate PSF of the imaging system. In order to restore the original appearance of the specimen under the conditions of the imaging system parameters are unknown or there is noise and spherical aberration in the system, a blind restoration methods of three-dimensional microscope based on the R-L algorithm is proposed in this paper. On the basis of the exhaustive study of the two-dimension R-L algorithm, according to the theory of the microscopy imaging and the wavelet transform denoising pretreatment, we expand the R-L algorithm to three-dimension space. It is a nonlinear restoration method with the maximum entropy constraint. The method doesn’t need to know the PSF of the microscopy imaging system precisely to recover the blur image. The image and PSF converge to the optimum solutions by many alterative iterations and corrections. The matlab simulation and experiments results show that the expansion algorithm is better in visual indicators, peak signal to noise ratio and improved signal to noise ratio when compared with the PML algorithm, and the proposed algorithm can suppress noise, restore more details of target, increase image resolution.

Citation Download Citation

Jin-li Yao, Si Tian, Xiang-rong Wang, and Jing-li Wang "Blind restoration method of three-dimensional microscope image based on RL algorithm", Proc. SPIE 8913, International Symposium on Photoelectronic Detection and Imaging 2013: Optical Storage and Display Technology, 89130Z (20 August 2013); https://doi.org/10.1117/12.2034965

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KEYWORDS

Point spread functions

Image restoration

Imaging systems

3D image processing

Microscopes

Signal to noise ratio

Microscopy

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