去散焦模糊的折反射全向成像系统设计

随着高分辨率传感器和大光圈的采用,光圈和反射面曲率造成的折反射全向成像散焦模糊问题越发突出。提出了一种有效去除散焦模糊的折反射全向成像系统设计。理论分析折反射成像散焦模糊的原因,建立全向图点扩展函数与实景空间物点及成像系统虚像位置的关系;在一次曝光成像时间内匀速旋转镜头对焦环,通过累积曝光使全向图散焦模糊核具有期望的空间不变性;利用反卷积算法对散焦模糊全向图进行复原,得到全局清晰的全向图像。该方法较好地解决了折反射全向成像散焦模糊问题,对提高折反射全向成像质量,促进其在相关领域的广泛应用具有重要意义。     

用神经网络鉴别退化图像的模糊类型

提出了一种用神经网络鉴别退化图像的模糊类型的方法。由于采用不同降质方法得到退化图像的频谱差异较大,以此作为判别依据,用概率神经网络实现了对四种模糊类型:离焦,矩形,运动和高斯模糊的鉴别。根据神经网络的鉴别结果决定点扩散函数的初始估计值,可大大地提高盲解恢复算法的复原质量和系统点扩散函数的估计精度,扩大了算法的实用范围。     

基于哈特曼-夏克波前传感器的模糊图像复原方法

离焦模糊图像的清晰度较低,因此必须对其进行复原。传统方法通常采用圆盘或高斯函数来近似离焦造成的点扩散函数,复原效果不够理想。为此,提出利用哈特曼-夏克波前传感器探测离焦波前,根据所得波前计算光学系统的点扩散函数,并采用Richardson-Lucy算法对模糊图像进行复原。搭建了实验用的光学系统,采集了离焦模糊图像以及相应的波前信息,获得了清晰的复原图像,并利用客观图像评价方法对退化图像和复原图像进行了评价,同时与传统方法得到的复原图像进行了比较。实验结果表明,该方法能精确重建点扩散函数,有效提高图像的质量。     

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.     

一种优化波前编码系统相位板参数的新方法

根据波前编码系统的设计理论,在兼顾图像恢复能力的基础上,提出利用不同离焦距离的点扩散函数与焦面处的点扩散函数之间的希尔伯特空间角作为成像特性一致性的评价函数,结合遗传算法,对扩大景深的波前编码成像系统的相位板参数进行优化。分别在空间域和频率域上分析应用波前编码技术前后光学系统的成像特性,并利用最小二乘数字滤波器对中间模糊图像进行复原。仿真实验结果表明:在三次相位板上应用此方法获得的最佳相位板参数使波前编码系统焦深扩展了10倍。     

A Robust Point Spread Function Estimation for Out-of-Focus Blurred and Noisy Images Based on a Distribution of Gradient Vectors on the Polar Plane

The estimation of the point spread function (PSF) is a very important and indispensable task for practical image restoration. Various PSF estimation algorithms have been developed, especially for the out-of-focus blur. However, a majority of them are useless in an extremely noisy environment. This paper describes a new robust PSF estimation algorithm based on a distribution of gradient vectors on the logarithmic amplitude spectrum mapped to the polar plane. The proposed algorithm can estimate the out-of-focus PSF accurately and robustly, even for an image highly corrupted by noise. The effectiveness of the proposed algorithm is verified by applying it to the PSF estimation for out-of-focus blurred and noisy images.     

一种混合模糊含噪图像的参数辨识方法

在航空摄影、景象匹配导航等领域,由光学相机采集的图像往往同时存在着运动模糊和散焦模糊。成像中的噪声进一步加大了混合模糊图像点扩展函数的参数辨识难度。提出了一种双谱混合模糊含噪图像的点扩展函数参数辨识方法。首先计算出经混合模糊后的标准测试图像所对应的运动和散焦模糊的双谱,然后通过曲线拟合出双谱中各自的统计特性与运动模糊尺度或散焦半径之间的函数关系,由此训练出的BP神经网络可以完成对其它含有噪声的混合模糊图像点扩展函数的参数辨识。实验结果表明,该方法适用于含有噪声的一定模糊参数范围内的混合模糊图像。在信噪比为25dB的情况下,辨别出的模糊参数偏差不超过0.5个像素。     

大焦深成像系统的特性研究

如何增大非相干光学成像系统的焦深已成为一项有意义的研究主题，为了增大焦深，通常的做法是缩小相对孔径，但这种做法会降低光学系统的光通量、调制传递函数（MTF）及分辨率，而大焦深成像系统通过在光学系统光路中加入一特殊设计的非球面掩摸板，并用图像处理技术对相位掩模板编码后的图像进行解码得到清晰图像，保证了光学系统在维持原有相对孔径的同时扩大其焦深范围，使光学系统在离焦范围内有好的图像质量，从光学图和系统的MTF两个方面对大焦深成像系统的特性进行了分离，并对结果进行了讨论。     

运动与离焦模糊图像的复原

在运动和离焦所引起的图像模糊的情况中,本文提出了一种新的基于霍夫变换区分离焦模糊和运动模糊两类模糊的方法.该方法通过比较霍夫变换矩阵中的亮点数来区分两类模糊,不仅正确率达到100%,而且抗干扰性能好;其次通过对运动模糊图像做两次方向微分,估计其模糊方向,提高了模糊方向的估计准确度;最后利用改进的Prewiit算子和费米函数计算模糊图像的刃边函数,进而得到图像的调制传递函数,再利用维纳滤波复原图像.实验结果表明:本文算法不仅具有有效性和强抗噪音能力,而且对图像的信噪比要求可以低到20 dB;与传统算法相比,提高了图像的复原质量.     

倒谱在混合模糊图像分析中的应用

降晰参数识别在模糊图像恢复过程中具有很重要的作用。在各种图像捕获系统中,有两种形式的图像模糊比较常见:一种是由光学系统散焦造成的散焦模糊;另一种是物体与照相机之间的相对运动造成的运动模糊。相对单个模糊模型的参数识别来说,混合了散焦和运动模糊的图像,其模糊参数的识别要复杂得多。许多识别方法一般都是用来分析某一特定的模糊模型的,而对两种模糊混合在一起的情况来说是很难区分的。提出了一种倒谱分析方法,在倒谱域同时对这两种模型参数进行识别。在分析过程中,仍需要利用这两种模糊模型在频域的特征,首先应用一些调整性的变换,然后再转换到倒谱域,以便更准确地评估模糊参数。     

Blur identification and restoration of degraded images using generalized cross-validation criterion

In this paper, we describe blur identification and restoration of noisy degraded images. The point-spread function (PSF) can be characterized by the quantity of blur. Thus the blur identification problem can be solved as a parameter estimation problem. The estimation method is a generalized cross-validation (GCV) criterion that is known as a powerful measure that can be used to choose the optimal regularization parameter without a priori knowledge about noise. We use the iterative damped-1east squares (DLS) algorithm which is based on the principle of damped least-squares for restoring noisy degraded images.     

Dielectric relaxation in polyvinylidenefluoride–polysulfone blends

Dielectric properties of polymer blend of polyvinylidenefluoride (PVDF) and polysulfone (PSF) of different wt. % have been studied to understand the molecular motion and their relaxation behavior in the frequency range of 100 Hz to 10 kHz at different temperatures between 30 and 190 °C. The dielectric constant of the blend decreased with frequency and increased with the increasing temperature and PSF content in the blend. The magnitude of dielectric loss also increased with increase in temperature and PSF content. The observed characteristic has been consistently explained in terms of dipolar motions and the plasticization effect brought about by blending of PSF with PVDF. At constant frequency and temperature, the blend follows a linear relationship between logarithm of their dielectric constant and different ratios of blend. The appearance of a peak for each concentration in dielectric loss suggests the presence of relaxing dipoles in the blend. In addition of PSF with PVDF, the peak shifts toward higher frequency side suggesting the speed up the relaxation process. AC dielectric data is also combined with thermally stimulated depolarization current (TSDC) data which is generally studied for low-frequency dielectric properties of polymers blends so as to produce the results in a wide frequency range. The glass transition temperature (T_g) of the blend was studied by differential scanning calorimetric technique (DSC), the T_g was compared and correlated with TSDC peak. The blend samples were characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM) to study the formation of blend and micro structural properties of the materials. The shifting of peak toward lower diffraction angle side confirms the reduction in particle size with increasing amorphous content in the blend.     

基于微分图像自相关的离焦模糊图像盲复原

针对离焦模糊图像的盲复原算法的研究具有重要的实际意义和实用价值.根据光学离焦成像模型,研究提出了一种基于微分图像自相关的离焦模糊图像超分辨力盲复原算法,即首先采用拉普拉斯算子对离焦模糊图像进行二阶微分并求微分图像的自相关,然后从自相关结果所包含的信息中确定离焦模糊半径,最后以离焦模糊模型结合MPMAP超分辨力复原算法对离焦模糊图像进行肓复原.实验证明:算法能够以较高的精度估计出离焦模糊半径并实现离焦模糊图像的盲复原,该算法较其它同类算法在减少计算过程中需要考虑的各类因素的同时也减少了计算量,提高了结果精度,依靠超分辨力复原算法获取更多的复原图像信息,已在实际刑侦和物证鉴定的离焦模糊图像判读和鉴定中获得成功应用.     

基于离焦的微操作机器人系统光轴方向深度测量

在分析显微物镜成像原理的基础上,提出并实现了一种微操作机器人系统光轴方向深度测量方法,该方法通过显微物镜离焦光学传递函数（optical transfer function, OTF）建立物方离焦程度与显微图像模糊程度的关系,由此实现深度测量.由于考虑了透镜参数与衍射效应的影响,方法具有较高的测量精度和较好的线性度,同时利用条状物体快速辨识算法,对原始方法进行了简化,使深度测量可在线完成.进一步,将上述方法应用于实际微操作机器人系统,通过离焦状态双针互插实验验证了方法的有效性,同时拓展了微操作机器人系统的有效操作空间. 关键词： 深度测量 微操作机器人 显微镜系统成像模型 光学传递函数     

点扩散函数高斯拟合估计与遥感图像恢复

为了减轻或消除航天遥感相机成像过程中图像退化造成的模糊,突出图像的特征目标,对获取的图像进行了恢复处理。首先,采用陷波滤波器在频率域对遥感图像进行了去噪预处理。然后,通过图像中具有刀刃边缘的地物估计成像系统的退化函数,即点扩散函数;同时,利用高斯拟合对估计的点扩散函数进行校正。最后,利用拟合后的点扩散函数,采用自适应维纳滤波对图像进行恢复。实验结果表明：陷波滤波器基本消除了图像中叠加的条带噪声。与原图相比,细节图像恢复后其方差增大4.395,灰度平均梯度增大1.799,Laplacian梯度增大10.014,图像目视效果更清晰。高斯拟合的点扩散函数用于遥感图像恢复,减轻了图像模糊,使图像细节突出,纹理清晰,利于图像的判读和分析。     

可调谐相位板空域频域联合分析

波前编码系统采用在传统光学系统中加入相位板来扩大光学系统的景深而避免传统景深延拓技术的不利影响. 由于相位板的参数不可调, 整个系统的景深延拓扩展率也不能动态可调. 采用两相位板组合的方法可以有效克服这一点. 本文首先从光线差的角度提出了两三次相位板组合下的光线像差分布以及点扩散函数尺寸的具体关系表达式, 直观体现了系统的光线结构, 指出了光线结构和点扩散函数尺寸受两三次相位板的面型和相对位移量的影响. 其次采用稳相法从空间域给出了系统点扩散函数表达式, 依据点扩散函数的振荡性质给出了有效带宽表达式, 提出了点扩散函数在像面的位置会随两相位板面型参数以及相对于光瞳中心的位移量而发生平移. 最后利用菲涅耳积分给出两三次相位板任意面型参数和相对位移组合下的准确光学传递函数. 在得到的调制传递函数中直观体现出了面型参数和相对位移量对调制传递函数和相位传递函数以及有效带宽的影响, 并说明了此系统相位传递函数的非线性性质. 通过空间域与频率域相结合的方法分析验证了传统的两三次相位板组合具有景深可调和带宽可调的性质, 为设计可调谐波前编码系统提供了理论依据.     

Comparison of point spread models for underwater image restoration

It is known that absorption and scattering properties of water are the main causes of blur in underwater images. With the knowledge of point spread function (PSF), the performance of underwater image restoration can be effectively enhanced, which will also extend the imaging range as well. The presented effort reviews several empirical PSF models and an imagery-derived approach based on image formation. Varied models are applied for blind deconvolution restoration, performance of which are compared and discussed. Models under comparison include the empirical models by Duntley, Voss, Wells, as well as the imagery-derived approach which can also provide adequate accuracy and flexibility for image restoration, as shown by experimental results.     

Analysis and modeling of radiometric error caused by imaging blur in optical remote sensing systems

Imaging blur changes the digital output values of imaging systems. It leads to radiometric errors when the system is used for measurement. In this paper, we focus on the radiometric error due to imaging blur in remote sensing imaging systems. First, in accordance with the radiometric response calibration of imaging systems, we provide a theoretical analysis on the evaluation standard of radiometric errors caused by imaging blur. Then, we build a radiometric error model for imaging blur based on the natural stochastic fractal characteristics of remote sensing images. Finally, we verify the model by simulations and physical defocus experiments. The simulation results show that the modeling estimation result approaches to the simulation computation. The maximum difference of relative MSE (Mean Squared Error) between simulation computation and modeling estimation can achieve 1.6%. The physical experimental results show that the maximum difference of relative MSE between experimental results and modeling estimation is only 1.29% under experimental conditions. Simulations and experiments demonstrate that the proposed model is correct, which can be used to estimate the radiometric error caused by imaging blur in remote sensing images. This research is of great importance for radiometric measurement system evaluation and application.     

Super-resolution by pupil plane phase filtering

Resolution capability of any optical imaging system is limited by residual aberrations as well as diffraction effects. Overcoming this fundamental limit is called super-resolution. Several new paradigms for super-resolution in optical systems use ‘a posteriori’ digital image processing. In these ventures the three-dimensional point spread function (PSF) of the lens plays a key role in image acquisition. A straightforward tailoring of the PSF can be performed by appropriate pupil plane filtering. With a brief review of the state-of-art in this research area, this paper dwells upon the inverse problem of global optimization of the pupil function by phase filtering in accordance with the desired PSF.     

基于相位相关的匀速直线运动模糊图像位移参数估计

为估算匀速直线运动模糊图像的运动参数,提出了一种基于相位相关分析的图像配准方法。该方法利用傅里叶变换的平移特性,对产生平移的目标图像进行傅里叶变换并计算归一化互功率谱,其傅里叶逆变换对应二维脉冲函数,通过计算脉冲函数峰值坐标获取位移图像之间的亚像元级位移量。结合相位相关配准原理和线性空间不变退化模型,给出了匀速直线运动点扩散函数及其光学传递函数的数学描述;讨论了匀速直线运动模糊对相位相关配准结果的影响,证明了图像经过匀速直线运动退化后,位移图像之间归一化互功率谱具有不变性。实验结果表明：动态运动模糊图像最大检测误差为0.489 pixel,标准差为0.16 pixel。