|其他题名: ||The Study on Blind Image Restoration Technologies in Imaging System
（4） 根据多通道图像退化模型，提出了短曝光序列多帧图像盲复原算法。利用极大似然估计原理，建立了Poisson模型下的多帧图像复原似然函数，并对其进行了优化改进，利用EM算法极大化似然函数，推出了EM迭代图像复原方法；结合离散点扩展函数（DPSF）估计的原理，提出了一种新算法——基于DPSF估计的多帧图像复原混合算法。新算法利用两帧短曝光图像估计出离散点扩展函数，并以此作为EM法图像复原的初始估计进行迭代图像复原，减少了原有多帧图像复原算法初始估计的盲目性， 增强了原有算法图像复原的收敛性和稳定性，加速了图像复原的进程，同时具有良好的抗噪性能以及超分辨率复原的能力。根据工程应用需求，提出了多帧图像复原算法实现的方案，为算法的硬件实现奠定了基础。
|英文摘要: ||Blind image restoration is a kind of key technology of restoring image quality and enhancing image definition. According to the requirement of real-time imaging system, the Ph D dissertation deep researched into the blind image restoration technologies of atmosphere turbulence-degraded image, motion blurred image, out-of-focus blurred image in imaging system, presented some new methods and technologies of blind image restoration, and obtained important progress.
To atmosphere turbulence-degraded image restoration, regarding enhancement of restored image quality and decrease of restoring time as the essential goal, the paper carried through deep researches from different point of views and brought forward some methods and technologies to resolve the problems of turbulence-degraded image restoration in actual imaging system.
(1) It is assumed that some short-exposure turbulence-degraded images have class G point spread function (PSF); accordingly the restoration algorithm for turbulence-degraded images based on APEX method is present. The algorithm estimates class G PSF by the frequency-domain information of turbulence-degraded image, then restores clear image. Considering the frequency-domain features of actually collected turbulence-degraded image, a new method is presented which synthetically estimates class G PSF by multi-direction one-dimension frequency spectrum. The new method decreases the affection of random disturbance, makes up the objection that original single-direction estimation of class PSF is instable. Thus, the stability and practicability of APEX method are greatly enhanced in real turbulence-degraded image restoration.
(2) On the condition that the parameter model of image degradation is unknown, the paper put forward the restoration method for turbulence-degraded image based on the estimation of discrete point spread function (DPSF). The method establishes the math model of DPSF estimation by the frequency-domain information of two short-exposure images, and estimates PSF by extremum optimization of an object function. The object function is improved by prior-constraint information, accordingly the precision of DPSF estimation is greatly enhanced, and the stability and reliability of image restoration are built up. It shortens image restoration time that the optimization estimation of DPSF is carried out by Newton iterative method.
(3) According to the principle to maximum likelihood, the paper brought forward blind image restoration algorithm of single-frame image based on maximum likelihood. The algorithm regards the original image and PSF as unknown parameter, establishes the optimization estimation model of blind image restoration, and changes the problem of image restoration into extremum optimization of object function. The image restoration is optimized by regularization technologies and priori-constraint information, which obviously enhances the stability and the capability of resisting-noise. Searching extremum by conjugate grads method, the algorithm present cross iterative estimation flow of image and PSF. An appropriate initial estimation of PSF accelerates the course of image restoration.
(4) According to the multi-channel image degradation model, the paper studied multi-frame images blind restoration algorithm for short-exposure sequence images. The maximum-likelihood function of multi-frame images restoration is established according to maximum-likelihood theory and Poisson probability model, and is improved by prior information. The maximum-likelihood function is maximized by EM algorithm; accordingly, EM iterative image restoration method is deduced. On basis of EM image restoration, combining the principle of estimating DPSF, the paper present a kind of blend method of multi-frame image restoration based on DPSF estimation, which estimates DPSF by two sequential images, and regards the DPSF as the initial estimation of EM image restoration, accelerates the course of EM image restoration, and have strong resist-noise capability and super-resolution performance. According to the requirement of engineering application, the realization project of multi-frame image restoration algorithm was designed, which established a firm foundation of hardware realization.
Concerning the motion blurring image with noise disturbance, the paper presented an algorithm of estimating motion parameter in the peak-trace domain. On condition of noise disturbance, the neighborhood of frequency-domain origin is defined as peak-trace domain, and the peak-trance direction is extracted in the peak-trace domain. According to the perpendicular relation between motion direction and peak-trace direction, the motion direction can be obtained. On the basis of motion direction, motion blurring length can be estimated. Consequently, motion blurring image with noise disturbance can be restored. The algorithm has better resist-noise performance and stronger practicability than traditional methods.
As for out-of-focus blurred image restoration, on the basis of disk out-of-focus model, the paper presented the blind image restoration algorithm based on kurtosis minimization. The algorithm gives up the idea of traditional method which estimates blurring radius by frequency-domain features. It restores blurred image by Wiener filter according to some blurring radius, and regards the restored image with minimum kurtosis as the final restored image, and successfully realizes the image restoration of out-of-focus blurred image with noise disturbance. According to the principle of rough focusing and accurate focusing, the paper put forward a new strategy of rough searching and accurate searching of blurring radius. Consequently the course of image restoration is greatly quickened.
According to the features of image in actual imaging system and requirement of actual engineering application, the paper brought forward some new methods and technologies of blind image restoration, which are proved to be effective in actual image restoration experiment, resolved the contradiction between blind restoration quality and restoration time to some extent, and established the theory basis by which blind image restoration technologies were applied into actual imaging system.|
|Appears in Collections:||光电技术研究所博硕士论文_学位论文|
|File Name/ File Size
谢盛华. 成像系统图像盲复原技术研究[D]. 光电技术研究所. 中国科学院光电技术研究所. 2007.