退化图像复原技术在天文图片处理中的应用

针对天文望远镜系统自身的焦散特性以及成像过程中高斯白噪声的影响,依据对透镜系统点扩散函数的先验知识,运用维纳滤波方法对退化的天文图片进行了复原处理。实验表明,这一方法能够对退化天文图片进行有效的复原,同时该处理方法对具有类似问题的光学成像系统的图像处理具有很好的借鉴意义。     

Modeling for edge detection problems in blurred noisy images

The aim of this paper is to provide a theoretical set up and a mathematical model for the problem of image reconstruction. The original image belongs to a family of two-dimensional (2-D) possibly discontinuous functions, but is blurred by a Gaussian point spread function introduced by the measurement device. In addition, the blurred image is corrupted by an additive noise. We propose a preprocessing of data which enhances the contribution of the signal discontinuous component over that one of the regular part, while damping down the effect of noise. In particular we suggest to convolute data with a kernel defined as the second order derivative of a Gaussian spread function. Finally, the image reconstruction is embedded in an optimal problem framework. Now convexity and compactness properties for the admissible set play a fundamental role. We provide an instance of a class of admissible sets which is relevant from an application point of view while featuring the desired properties.     

空间变化离焦模糊红外图像快速复原算法

为了提升空间变化离焦模糊红外图像的图像质量,提出了一种基于图像质量评价的快速复原算法.本文提出的方法首先对模糊图像采用不同点扩散函数对应的截断约束最小二乘法算法进行复原而获得多幅复原图像,并对复原图像进行去振铃;然后对复原图像中每个像素为中心的区域进行图像质量评价,将采用不同参数复原的图像以图像质量评价的结果进行组合以...     

Blind blur assessment for vision-based applications

In this paper, a criterion for objective defocus blur measurement is theoretically derived from one image. The essential idea is to estimate the point spread function (PSF) from the line spread function (LSF), whereas the LSF is constructed from edge information. It is proven that an edge point corresponds to the local maximal gradient in a blurred image, and therefore edges can be extracted from blurred images by conventional edge detectors. To achieve high accuracy, local Radon transform is implemented and a number of LSFs are extracted from each edge. The experimental results on a variety of synthetic and real blurred images validate the proposed method. The algorithm can be implemented for image quality evaluation in vision-based applications as no reference images are needed.     

基于位平面分解方法的运动模糊图像PSF参数辨识

在基于匀速直线运动的运动模糊图像的复原中,点扩散函数(PSF)的两个参数(运动模糊角度和运动模糊尺度)的估计是研究的重点.为了能够准确地估计出PSF的模糊角度,提出了在一种新的改进倒频谱域中采用位平面分解提取和Radon变换相结合的方法.并在已知运动模糊角度的基础上再对模糊图像采用差分自相关处理,得到运动模糊尺度.将上述整个算法用Matlab进行仿真实验.实验结果表明:该算法在获取运动模糊参数的效率和准确度方面较现有文献的同类算法有所提高,得到的复原图像也更加清晰.     

任意方向匀速直线运动模糊的点扩展函数估计

在运动图像复原中,建立图像退化模型的关键是找到准确的点扩展函数(PSF)。提出了一种基于单幅图像的、改进的任意方向匀速直线运动模糊PSF的估计方法。利用基于图像频谱亮线灰度特征的方向鉴别方法鉴别模糊图像的模糊方向,利用微分自相关的方法对模糊图像的模糊尺寸进行计算,通过计算模糊图像沿二维直线运动方向不同距离的重叠度,来计算得到相应的PSF。通过开展仿真分析和成像实验,演示了PSF估计和图像复原过程。通过采用图像质量评价函数,将图像复原结果与现有算法进行对比,验证了所提出方法的有效性。     

薄雾模糊图像的恢复算法研究

成像光波受到大气中薄雾干扰,形成模糊图像。文章基于最大熵算法,分析了成像系统点扩展函数畸变导致图像模糊的机理,提出了一种有效的薄雾模糊图像的恢复算法。     

Reducing chemical shift artifacts in MRI in time-varying gradients

An image processing algorithm to reduce chemical shift artifacts in MRI (magnetic resonance imaging) with time-varying gradients and to obtain the chemical shift images without increasing the imaging time is presented. It is known that when both gradients in two directions of the imaging plane are time-varying, such as in the spiral-type scanning MRI, the chemical shift artifacts appear as a blurred image. The artifacts cannot be neglected, since the total power of the out-of-focus point spread function (PSF) for the blurred image equals that of the in-focus PSF. The proposed algorithm separates the chemical shift images by iteratively estimating the artifacts under an a priori constraint that the original images should have a real and nonnegative value. Computer simulation results show that the average amplitude of the artifacts can be reduced significantly after several iterations, and that the algorithm works well even when the observation noise exists.     

航天时间延迟积分CCD相机振动模糊图像的恢复

提出了一种对航天时间延时积分(TDI)电荷耦合器件(CCD)相机振动移变降质图像进行恢复的方法。首先介绍了TDI-CCD的工作原理及其对振动的敏感性,建立了TDI-CCD振动降质的点扩散函数(PSF)模型,指出振动对TDI-CCD相机的降质过程是空间移变的;然后提出了基于快速CCD的振动检测方法,在振动检测技术中,利用了一种改进的灰度投影算法计算振动参量;最后提出对降质图像进行逐行恢复的方法,并对模糊图像进行了恢复。分别对匀速直线运动和正弦振动进行了实验。用峰值信噪比(PSNR)作为评价标准,对恢复图像进行了评价。结果表明,匀速直线运动模糊图像的PSNR为33.98dB,恢复后其PSNR为41.14dB;正弦振动模糊图像的PSNR为39.68dB,恢复后其PSNR为45.12dB。     

High-quality non-blind image deconvolution with adaptive regularization

Non-blind image deconvolution is a process that obtains a sharp latent image from a blurred image when a point spread function (PSF) is known. However, ringing and noise amplification are inevitable artifacts in image deconvolution since perfect PSF estimation is impossible. The conventional regularization to reduce these artifacts cannot preserve image details in the deconvolved image when PSF estimation error is large, so strong regularization is needed. We propose a non-blind image deconvolution method which preserves image details, while suppressing ringing and noise artifacts by controlling regularization strength according to local characteristics of the image. In addition, the proposed method is performed fast with fast Fourier transforms so that it can be a practical solution to image deblurring problems. From experimental results, we have verified that the proposed method restored the sharp latent image with significantly reduced artifacts and it was performed fast compared to other non-blind image deconvolution methods.     

基于参数估计的降晰函数辨识及图像复原算法

成像系统的点扩展函数(PSF)以及观测噪声,在一般应用过程中是未知信息,因此,点扩展函数的辨识是一个具有挑战性的世界难题.为解决实际工作中遇到的在已知降晰类型情况下的降晰函数辨识和降晰图像复原问题,提出了基于参数估计的降晰函数辨识及降晰图像复原算法.首先,由初始猜测给定降晰函数参数的变化范围和参数的增量步长;然后,最小化降晰图像和由相应点扩展函数及降晰图像得到的实验观测图像的差的Frobenius范数,以确定点扩展函数的参数,进而确定降晰图像的点扩展函数并对降晰图像进行复原.应用基于Wiener滤波的频域循环边界算法对降晰图像进行复原.实验结果表明:在降晰图像信噪比较高的情况下,降晰函数的辨识结果是可靠和准确的,有较好的复原效果.     

Radon变换和全变分相融合的图像复原算法

图像复原的核心是点扩散函数的估计和直接去卷积算法,针对拍照过程中,相机和被拍摄物体由于相对运动而导致的图像退化问题,提出一种基于Radon变换和全变分相融合的图像复原算法。首先利用radon变换对图像退化模型参数进行估计,然后采用全变分算法复原退化图像,最后在Matlab 2012平台进行仿真实验对算法的性能检验。仿真结果表明,相对于其它图像复原算法,本文算法可以准确估计退化模型参数,获得了更加理想的图像复原效果,具有一定的实际利用价值。     

Identification and restoration of spatially variant motion blurs insequential images

Sequential imaging cameras are designed to record objects in motion. When the speed of the objects exceeds the temporal resolution of the shutter, the image is blurred. Because objects in a scene are often moving in different directions at different speeds, the degradation of a recorded image may be characterized by a space-variant point spread function (PSF). The sequential nature of such images can be used to determine the relative motion of various parts of the image. This information can be used to estimate the space-variant PSF. A modification of the Landweber iteration is developed to utilize the space-variant PSF to produce an estimate of the original image.     

Fast magnetic resonance imaging with simultaneously oscillating and rotating fiell gradients

We present an approach to magnetic resonance imaging employing a magnetic field gradient that rotates 180 degrees in the image plane while the gradient magnitude oscillates rapidly during the rotation. A single free induction decay recorded during this rotation contains all the information needed to reconstruct a two-dimensional image. In effect, each sinusoidal oscillation of the gradient provides information corresponding to one projection in more conventional Fourier-projection approaches. Since the data acquisition can be achieved in a period less than T2, the method offers the potential of great speed, which is limited only by the gradient modulation frequency. An explicit image reconstruction formula is derived that gives, when evaluated, a reconstruction of the magnetization equal to the true magnetization convolved with a space-invariant point spread function. This point spread function is derived and characterizes the resolving power and sidelobe response of the technique. Moreover, we derive a similar reconstruction formula which is valid when known inhomogeneities in the static field H0 and T2 are present. Finally, we show how the general approach can be extended to three dimensions.     

长曝光大气湍流退化图像点扩散函数估计

大气湍流能明显降低光学系统的成像质量,距离目标越远,曝光时间越长,受大气扰动越严重,图像越模糊。利用大气湍流退化点扩散函数可以对模糊图像进行复原,但实际自然条件下的点扩散函数往往难以准确获得。结合课题研究背景,针对长曝光大气湍流退化图像复原提出了近似等腰三角形模型,通过该模型能得到准确的大气湍流点扩散函数,并采用维纳滤波获得清晰复原图像。实验表明该方法能够对大视场、远距离条件下获得的长曝光大气湍流退化自然图像估计出准确的点扩散函数,复原图像拥有较好的视觉效果,通过计算灰度平均梯度值和拉普拉斯梯度模两个客观评价标准,进一步证实了该算法的有效性。     

A novel blind deconvolution scheme for image restoration usingrecursive filtering

We present a novel blind deconvolution technique for the restoration of linearly degraded images without explicit knowledge of either the original image or the point spread function. The technique applies to situations in which the scene consists of a finite support object against a uniformly black, grey, or white background. This occurs in certain types of astronomical imaging, medical imaging, and one-dimensional (1-D) gamma ray spectra processing, among others. The only information required are the nonnegativity of the true image and the support size of the original object. The restoration procedure involves recursive filtering of the blurred image to minimize a convex cost function. We prove convexity of the cost function, establish sufficient conditions to guarantee a unique solution, and examine the performance of the technique in the presence of noise. The new approach is experimentally shown to be more reliable and to have faster convergence than existing nonparametric finite support blind deconvolution methods. For situations in which the exact object support is unknown, we propose a novel support-finding algorithm     

基于梯度倒频和全变分的运动模糊图像复原

通过分析运动模糊图像梯度和Canny算子特性来估算点扩算函数(PSF),提出一种基于结合Canny算子和梯度倒频的运动模糊参数先验估计方法.首先,分析运动模糊图像的梯度信息和Canny算子特性,通过适当的阈值处理后,二者信息结合,利用倒频谱的特性计算出运动模糊尺度和运动模糊方向.最后,用改进的基于半二次型交替数值算法的全变分正则化复原方法对运动模糊图像进行复原.从实验结果可以看出,相对于传统算法,该方法能够较准确地估算出PSF参数,实现比较好的复原效果.     

基于匀速直线运动下模糊图像复原的研究

根据运动模糊图像产生的原因及特点,文中阐述了在匀速直线运动下模糊图像退化的模型,介绍了维纳滤波复原图像的原理。由于在图像获取时模糊原因的不确定性,使得点扩散函数(PSF)具有不准确性,从而使模糊图像复原的效果不佳。针对点扩散函数的确定,利用方向微分法快速判断运动模糊方向,再利用一阶差分自相关的方法鉴定运动模糊图像的模糊尺度,从而确定点扩散函数。在确定K值时,采用K值自动估计算法。通过实验仿真表明,此方法对模糊图像复原效果良好。     

Blind image restoration with eigen-face subspace.

Performance of conventional image restoration methods is sensitive to signal-to-noise ratios. For heavily blurred and noisy human facial images, information contained in the eigen-face subspace can be used to compensate for the lost details. The blurred image is decomposed into the eigen-face subspace and then restored with a regularized total constrained least square method. With Generalized cross-validation, a cost function is deduced to include two unknown parameters: the regularization factor and one parameter relevant to point spread function. It is shown that, in minimizing the cost function, the cost function dependence of any one unknown parameter can be separated from the other one, which means the cost function can be considered roughly, depending on single variable in an iterative algorithm. With realistic constraints on the regularized factor, a global minimum for the cost function is achieved to determine the unknown parameters. Experiments are presented to demonstrate the effectiveness and robustness of the new method.     

Focused image recovery from two defocused images recorded withdifferent camera settings

Two new methods are presented for recovering the focused image of an object from only two blurred images recorded with different camera parameter settings. The camera parameters include lens position, focal length, and aperture diameter. First a blur parameter sigma is estimated using one of our proposed depth-from-defocus methods. Then one of the two blurred images is deconvolved to recover the focused image. The first method is based on a spatial domain convolution/deconvolution transform. This method requires only the knowledge of sigma of the camera's point spread function (PSF). It does not require information about the actual form of the camera's PSF. The second method, in contrast to the first, requires full knowledge of the form of the PSF. As part of the second method, we present a calibration procedure for estimating the camera's PSF for different values of the blur parameter sigma. In the second method, the focused image is obtained through deconvolution in the Fourier domain using a Wiener filter. For both methods, the results of experiments on actual defocused images recorded by a CCD camera are given. The first method requires much less computation than the second method. The first method gives satisfactory results for up to medium levels of blur and the second method gives good results for up to relatively high levels of blur.