In the digital confocal microscopy technology, voltage ceramic is used to drive axial moving of objective lens to collect
image slices, which is simple and flexible, easy to control and will get a large precision. But as a result of the movement,
the corresponding parameters of the system, even the point spread function changes, which will bring error to the image
restoration. According to the principle of optical imaging, the change of the point spread function is quantitative
calculated in this paper, through the experiment of recover the image slices collected by moving objective lens and the
image slices collected by moving the loading platform, the error is calculated, compared and analyzed. The results can
verify the feasibility of moving lens to collect image slices.
Based on the cartesian coordinate system, a coaxial couple cartesian coordinate system is designed whose z-axis is
coaxial but z-axis coordinate is independent, and its xy plane is different but coordinate is the same. The object
space and the image space are set in the two sub-cartesian coordinates respectively. In the coaxial couple cartesian
coordinate system, according to the principle of optical imaging, a form of the optical microscope's imaging model
of optical sectioning biological thick specimen is derived. The model form show that if a biological thick specimen
is expressed as a pile of slices with tiny interval, and a slice among the slices is put in microscope's focal plane, then
the thick specimen's image in image plane is the superposition of the focal plane image and all of the defocus images.
In the model form, thick specimen's image is simply sorted into focal plane image and defocus image to make it
easy to look insight, so the model clearly reflects the imaging relationship between the slice of thick specimen, and it
is conducive to the analysis of the microscope's imaging characteristics for thick specimen. And the stack of optical
section according to the model is equivalent to the mathematical model of three-dimensional imaging of thick
specimen.
KEYWORDS: Image restoration, 3D image processing, 3D image reconstruction, Wavelets, Signal to noise ratio, 3D image restoration, Biological research, Convolution, Image processing, Super resolution
A method is proposed for adaptively choosing local regularization parameter based on gray scale difference estimation, and used to
three-dimensional (3D) biological microscopic image restoration MPMAP algorithm. Every optical-sectioning image of 3D
microscopic image with noise is decomposed in wavelet domain, and then its high frequency images of horizontal , vertical and
diagonal direction are reconstructed. Then the images are convoluted respectively with corresponding direction operator, and the local
gray scale differences of high frequency images before and after convolution are calculated. The minimum of corresponding local
gray scale differences in the high frequency images is selected as local gray scale difference estimations of the optical-sectioning
image, then the local regularization parameter of the optical-sectioning image is chosen by mapping local gray scale difference
estimation. The local regularization parameter of the 3D microscopic image is made of the local regularization parameters of every
optical-sectioning image. The test results show that the local regularization parameter based on gray scale difference estimation can
describe more accurately intensity and position of noises than noise variance estimation. The local regularization parameter is used to
3D biological microscopic image regularization restoration with MPMAP algorithm. Experimental results show that better
super-resolution effect is reached than whole regularization parameter MPMAP.
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