谱域光学相干层析系统中基于解卷积方法的像质优化

谱域光学相干层析（spectral domain optical coherence tomography, 简记为SD-OCT）系统的轴向点扩散函数（point spread function, 简记为PSF）并不具备空不变特性,无法直接应用于解卷积运算.为实现SD-OCT系统成像质量基于解卷积算法的优化,本文采用数值校正后的轴向扫描信号和轴向有效PSF来实施基于Lucy-Richardson算法的解卷积运算,进而实现了SD-OCT系统中图像质量尤其是轴向分辨率的改善.本文理论分析了SD-OCT系统中导致轴向有效PSF随成像深度增大而下降和图像模糊的因素,阐述了利用解卷积算法实现图像质量优化的过程,基于建立的SD-OCT系统实施了不同成像深度位置处PSF的标定,并利用离散轴向位置处PSF的峰值拟合了轴向有效PSF的调制函数.利用调制函数对所有轴向扫描信号进行数值校正,然后根据轴向有效PSF进行解卷积算法.典型样品的解卷积图像重建结果表明,提出的解卷积方法能有效提高系统的轴向分辨率,同时有效抑制系统灵敏度随成像深度增大而下降的趋势. 关键词： 谱域光学相干层析 Lucy-Richardson解卷积 有效点扩散函数     

谱域光学相干层析系统中基于解卷积方法的像质优化

谱域光学相干层析（spectral domain optical coherence tomography, 简记为SD-OCT）系统的轴向点扩散函数（point spread function, 简记为PSF）并不具备空不变特性,无法直接应用于解卷积运算.为实现SD-OCT系统成像质量基于解卷积算法的优化,本文采用数值校正后的轴向扫描信号和轴向有效PSF来实施基于Lucy-Richardson算法的解卷积运算,进而实现了SD-OCT系统中图像质量尤其是轴向分辨率的改善.本文理论分析了SD-OCT系统中导致轴向有效PSF随成像深度增大而下降和图像模糊的因素,阐述了利用解卷积算法实现图像质量优化的过程,基于建立的SD-OCT系统实施了不同成像深度位置处PSF的标定,并利用离散轴向位置处PSF的峰值拟合了轴向有效PSF的调制函数.利用调制函数对所有轴向扫描信号进行数值校正,然后根据轴向有效PSF进行解卷积算法.典型样品的解卷积图像重建结果表明,提出的解卷积方法能有效提高系统的轴向分辨率,同时有效抑制系统灵敏度随成像深度增大而下降的趋势.     

Application of multi-frame approach in single-frame blind deconvolution

A new single-frame blind deconvolution algorithm for the linear shift-invariant imaging system is presented. The algorithm processes the partial images segmented from one single degraded image by multi-frame approach to recover the point spread function (PSF). Then a deconvolution method is employed to restore the whole image with the recovered PSF. In addition, in order to improve the fidelity and resolution of the recovered PSF, the coprimeness of the partial images is utilized. Results of simulated and real atmospheric turbulence degraded images using the algorithm are reported.     

最近邻域与无邻域算法结合空间滤波实现显微光切片

运用最近邻域与无邻域算法,并结合空间滤波方法,可去除显微切层图像的离焦模糊成份,可获得高成像速度、高质量的显微光切片。对各种显微图像进行了光切片处理,并与由现有去卷积处理、结构光照明等方法获得的光切片图像进行了对比,验证了该算法在去除模糊信息方面有更好的效果,提高了图像处理效率,获得了令人满意的光切片图像。在此基础上研制出了显微光切片图像处理系统。运用最近邻与无最近邻算法,结合空间滤波方法,采用简便可调的卷积模糊算子代替点扩散函数的估计过程,图像处理方便快捷,可较好地去除离焦平面的模糊信息。     

Relative focus map estimation using blind deconvolution

An automatic focus map extraction method is presented that uses a modification of blind deconvolution for estimation of localized blurring functions. We use these local blurring functions [so-called point-spread functions (PSFs)] for extraction of focus areas on ordinary images. In this inverse task our goal is not image reconstruction but the estimation of localized PSFs and the relative focus map. Thus the method is less sensitive than general deconvolution is to noise and ill-posed deconvolution problems. The focus areas can be estimated without any knowledge of the shooting conditions or of the optical system used.     

Gradient-Based Blind Deconvolution with Phase Spectral Constraints

This paper proposes a new blind deconvolution method with additional phase spectral constraints for a blurred image. A degradation of an original image is mathematically modeled by a convolution of an original image and a point-spread function (PSF). The proposed method consists of the following three steps: (i) projection onto a complex set satisfying the phase spectral constraint in a frequency space; (ii) minimization of a cost function preserving the constrained phase spectra; and (iii) projection onto an image space satisfying nonnegative and support constraints. This method restores both the original image and the PSF with high accuracy. The effectiveness of the proposed method is verified by applying it to some blind deconvolution problems for digital images, and the experimental results show that the performance is superior to the conventional blind deconvolution methods.     

Single image motion deblurring: An accurate PSF estimation and ringing reduction

In this paper we have proposed a single image motion deblurring algorithm that is based on a novel use of dual Fourier spectrum combined with bit plane slicing algorithm and Radon transform (RT) for accurate estimation of PSF parameters such as, blur length and blur angle. Even after very accurate PSF estimation, the deconvolution algorithms tend to introduce ringing artifacts at boundaries and near strong edges. To prevent this post deconvolution effect, a post processing method is also proposed in the framework of traditional Richardson–Lucy (RL) deconvolution algorithm. Experimental results evaluated on the basis of both qualitative and quantitative (PSNR, SSIM) metrics, verified on the dataset of both grayscale and color blurred images show that the proposed method outperforms the existing algorithms for removal of uniform blur. A comparison with state-of-the-art methods proves the usefulness of the proposed algorithm for deblurring real-life images/photographs.     

三维显微图像复原及点扩散函数的研究

三维显微图像去卷积计算量巨大,运算时间长。评价和分析了三维点扩散函数、散焦像、光学切片以及不同三维点扩散函数去卷积的复原图像,进一步证明了散焦光信息对焦面像的干扰,主要来自于焦面像两侧附近的散焦像。提出了折中选择三维PSF的空间大小,可以获得良好的复原效果,并且减少运行时间。提出了频谱图均值的新概念,作为评价图像清晰及模糊程度的标准,并运用于散焦像、光学切片以及复原结果图的评价。     

Multi-frame partially saturated images blind deconvolution

When blurred images have saturated or over-exposed pixels, conventional blind deconvolution approaches often fail to estimate accurate point spread function (PSF) and will introduce local ringing artifacts. In this paper, we propose a method to deal with the problem under the modified multi-frame blind deconvolution framework. First, in the kernel estimation step, a light streak detection scheme using multi-frame blurred images is incorporated into the regularization constraint. Second, we deal with image regions affected by the saturated pixels separately by modeling a weighted matrix during each multi-frame deconvolution iteration process. Both synthetic and real-world examples show that more accurate PSFs can be estimated and restored images have richer details and less negative effects compared to state of art methods.     

A piecewise local regularized Richardson-Lucy algorithm for remote sensing image deconvolution

As it is not possible to obtain an accurate point spread function (PSF) in remote sensing imaging, classic deconvolution methods such as Wiener filtering often introduce strong noise and ringing artifacts, which contaminate the restored images. In this paper, we modify the standard Richarson-Lucy (RL) algorithm with a piecewise local regularization term and combine it with residual deconvolution method. Experimental results show that it is effective in suppressing negative effects, and images with rich details and sharp edges are obtained.     

The beam-based calibration of an X-ray pinhole camera at SSRF

A pinhole camera for imaging X-ray synchrotron radiation from a dipole magnet is now in operation at the Shanghai Synchrotron Radiation Facility (SSRF) storage ring. The electron beam size is derived by unfolding the radiation image and the point spread function (PSF) with deconvolution techniques. The performance of the pinhole is determined by the accuracy of the PSF measurement. This article will focus on a beam-based calibration scheme to measure the PSF system by varying the beam images with different quadrupole settings and fitting them with the corresponding theoretical beam sizes. Applying this method at SSRF, the PSF value of the pinhole is revised from 37 to 44 μm. The deviation in beam size between the theoretical value and the measured value is minimized to 4% after calibration. This optimization allows us to observe the horizontal disturbance due to injection down to as small as 0.5 μm.     

PET image reconstruction with a system matrix containing point spread function derived from single photon incidence response

A point spread function(PSF)for the blurring component in positron emission tomography(PET)is studied.The PSF matrix is derived from the single photon incidence response function.A statistical iterative reconstruction(IR)method based on the system matrix containing the PSF is developed.More specifically,the gamma photon incidence upon a crystal array is simulated by Monte Carlo(MC)simulation,and then the single photon incidence response functions are calculated.Subsequently,the single photon incidence response functions are used to compute the coincidence blurring factor according to the physical process of PET coincidence detection.Through weighting the ordinary system matrix response by the coincidence blurring factors,the IR system matrix containing the PSF is finally established.By using this system matrix,the image is reconstructed by an ordered subset expectation maximization(OSEM)algorithm.The experimental results show that the proposed system matrix can substantially improve the image radial resolution,contrast,and noise property.Furthermore,the simulated single gamma-ray incidence response function depends only on the crystal configuration,so the method could be extended to any PET scanner with the same detector crystal configuration.     

基于目标和点扩展函数联合估计的点源目标图像近视解卷积

在传统的基于波前探测的解卷积方法中,由波前探测得到的点扩展函数被认为是精确的,并用维纳滤波进行复原,但是点扩展函数不可避免地存在误差,所以最终的复原目标图像质量不佳.为了解决该难题,提出了基于目标和点扩展函数联合估计的图像近视解卷积算法.它运用了点扩展函数和目标的先验信息,对点扩展函数和目标进行了规整和进一步约束,从而得到更优的恢复图像质量.对该方法的原理和实现过程进行了阐述,并将其运用于室内点源目标数据中.实验结果证明,与维纳滤波方法相比,该方法使图像恢复的效果得到明显改善.     

Blind image deconvolution using the zero-lag slice of higher-order statistics

A novel algorithm for blind image deconvolution using the zero-lag slice (ZLS) of higher-order statistics only is presented. This method first estimates the point-spread function (PSF) using the ZLS of its third-order moment (TOM) and then uses it with one of the known classical image deconvolution methods. The proposed method has simple computations for PSF estimation because it solves a nonlinear problem by using an iterative method with fast convergence. In each iteration, one need only calculate the ZLS of the TOM and estimate the PSF using simple two-dimensional operations. Furthermore, the method presented achieves good results, since the ZLS estimate obtained from the degraded image exhibits high reliability. The good performance of the proposed algorithm is demonstrated by applying it to synthetic and real data sets.     

Feasibility of infrared Earth tracking for deep-space optical communications

Infrared (IR) Earth thermal tracking is a viable option for optical communications to distant planet and outer-planetary missions. However, blurring due to finite receiver aperture size distorts IR Earth images in the presence of Earth's nonuniform thermal emission and limits its applicability. We demonstrate a deconvolution algorithm that can overcome this limitation and reduce the error from blurring to a negligible level. The algorithm is applied successfully to Earth thermal images taken by the Mars Odyssey spacecraft. With the solution to this critical issue, IR Earth tracking is established as a viable means for distant planet and outer-planetary optical communications.     

Spectral semi-blind deconvolution with hybrid regularization

A spectral semi-blind deconvolution with hybrid regularization (SBD-HR) is proposed to recover the spectrum and to estimate the parameter of the point spread function (PSF) adaptively. Firstly, a weighted Tikhonov regularization term about the spectrum is presented to preserve the details of spectrum. Then the regularization term about the PSF is modeled as L1-norm instead of L2-norm to enhance the stability of kernel estimation. The numerical solution processes for recovering the spectrum and for estimating the parameter of the PSF are deduced. Simulation results of infrared spectrum deconvolution demonstrate that the proposed method can recover the spectrum better from the degraded spectrum and estimate the parameter of the PSF accurately.     

Blind image deconvolution using the Fields of Experts prior

In this paper, we present a method for single image blind deconvolution. To improve its ill-posedness, we formulate the problem under Bayesian probabilistic framework and use a prior named Fields of Experts (FoE) which is learnt from natural images to regularize the latent image. Furthermore, due to the sparse distribution of the point spread function (PSF), we adopt a Student-t prior to regularize it. An improved alternating minimization (AM) approach is proposed to solve the resulted optimization problem. Experiments on both synthetic and real world blurred images show that the proposed method can achieve results of high quality.     

联合梯度预测与导引滤波的图像运动模糊复原

针对由相机与所摄景物之间发生相对位置移动所导致的图像运动模糊,提出了一种鲁棒的基于单幅运动模糊图像的盲反卷积算法。该方法首先通过预测图像中的较强边缘信息,实现用简单、易于求解的优化问题在傅里叶域中快速、准确地估计出点扩散函数。然后利用得到的点扩散函数,使用基于梯度约束的非盲反卷积算法复原清晰图像,同时采用一种新的边缘保持滤波器-导引滤波来消除噪声并抑制振铃效应。实验结果表明：本文的算法能够快速地从单幅运动模糊图像复原出具有清晰边缘和纹理的高质量图像,并且运算时间不超过20 s。     

空间变化PSF非盲去卷积图像复原法综述

传统的图像复原一般认为点扩散函数(PSF)是空间不变的,实际光学系统由于受到像差等因素的影响,并非严格的线性空间不变系统,基于空间变化PSF的非盲去卷积图像复原法逐渐体现其优越性。空间变化PSF的非盲去卷积图像复原法先准确估计图像空间变化的PSF,再利用非盲去卷积算法对图像进行复原,有利于恢复出高质量图像。本文从算法的角度综述了近几年提出的基于空间变化PSF的非盲去卷积图像复原方法,并对比了基于强边缘预测估计PSF的非盲去卷积法、基于模糊噪声图像对PSF估计非盲去卷积法等算法的优缺点,各算法分别在PSF估计精确度、振铃效应抑制效果、适用范围等方面体现出各自的优劣。空间变化PSF的非盲去卷积图像复原法的研究,有利于推进图像复原技术向更高水平发展,使光学系统往轻小型化方向发展,从而在多个科学领域发挥其重要作用。     

Centric scan SPRITE magnetic resonance imaging: optimization of SNR, resolution, and relaxation time mapping

Two strategies for the optimization of centric scan SPRITE (single point ramped imaging with T1 enhancement) magnetic resonance imaging techniques are presented. Point spread functions (PSF) for the centric scan SPRITE methodologies are numerically simulated, and the blurring manifested in a centric scan SPRITE image through PSF convolution is characterized. Optimal choices of imaging parameters and k-space sampling scheme are predicted to obtain maximum signal-to-noise ratio (SNR) while maintaining acceptable image resolution. The point spread function simulation predictions are verified experimentally. The acquisition of multiple FID points following each RF excitation is described and the use of the Chirp z-Transform algorithm for the scaling of field of view (FOV) of the reconstructed images is illustrated. Effective recombination of the rescaled images for SNR improvement and T*2 mapping is demonstrated.