Single-shot blind uniform motion deblurring with ringing reduction

In this paper, we have proposed a blind motion deblurring algorithm that comprises the estimation of the motion blur parameters (length and angle) in a modified cepstrum domain with a blind no-reference image spatial quality evaluator (BRISQUE) used for the tuning of point spread function (PSF) parameters. Ringing artifacts are generated during the deblurring process. In this paper, the modified R–L (Richardson–Lucy) algorithm with weight calculation based on graphcut is presented to obtain good estimates of the unblurred image with ringing reduction. The method involves the selection of different weights for edges and smooth regions such that the ringing effect over R–L iterations can be reduced. A newly proposed method has been tested on various natural images with a motion blur of different length and degrees. A comparison with state-of-the-art methods proves that the proposed technique achieved better results in terms of different quality measures such as SSIM, FSIM and PSNR and can be greatly beneficial for deblurring purpose.     

Parametric blind deconvolution: a robust method for the simultaneous estimation of image and blur.

Blind-deconvolution microscopy, the simultaneous estimation of the specimen function and the point-spread function (PSF) of the microscope, is an underdetermined problem with nonunique solutions that are usually avoided by enforcing constraints on the specimen function and the PSF. We derived a maximum-likelihood-based method for blind deconvolution in which we assume a mathematical model for the PSF that depends on a small number of parameters (e.g., less than 20). The algorithm then estimates the unknown parameters together with the specimen function. The mathematical model ensures that all the constraints of the PSF are satisfied, and the maximum-likelihood approach ensures that the specimen is nonnegative. The method successfully estimates the PSF and removes out-of-focus blur. The PSF estimation is robust to aberrations in the PSF and to noise in the image.     

Appearance of images through a multifocal intraocular lens

The appearance of images through a multifocal intraocular lens (IOL) was simulated. The optical transfer function (OTF) of a model eye containing the multifocal lens was measured and divided by the OTF of the model eye with a monofocal IOL. This ratio was used to filter digital images, generating simulations that represent the retinal images seen through a multifocal intraocular lens when viewed through an eye with a monofocal lens. A dichoptic side-by-side display was used to present the original image to one eye, implanted with the multifocal lens, while the other eye, implanted with monofocal lens, viewed the simulations and variations on the simulations to derive a point of subjective equivalence. Four subjects with such bilateral lens implants were tested for near and distance vision. The results validate the test methodology and the simulations. Referenced to the nominal theoretical filter, the prediction was within a 0.25-diopter (D) blur for distance simulation and within a 0.50-D blur for the near-vision simulation.     

基于APEX算法改进的图像复原算法

在高斯类点扩函数退化图像复原的研究中,提出了一种基于降晰图像频谱特征改进的APEX图像复原算法.该算法采用APEX算法的基本原理,根据图像频谱信息特征,对点扩散函数(PSF)估计过程进行了改进,采用加权最小二乘算法拟合出降晰图像频谱主方向,采用图像频谱主方向上的数据进行PSF估计,以利用更多的有效数据,从而减少PSF的估计误差.针对模拟和实际采集的降晰图像进行实验,采用主观视觉和峰值信噪比进行评价.实验结果表明,改进的算法较使用非主频谱方向上的频谱数据的复原算法在复原效果上有一定的提高.     

Approach for reconstructing anisoplanatic adaptive optics images

Atmospheric turbulence corrupts astronomical images formed by ground-based telescopes. Adaptive optics systems allow the effects of turbulence-induced aberrations to be reduced for a narrow field of view corresponding approximately to the isoplanatic angle theta(0). For field angles larger than theta(0), the point spread function (PSF) gradually degrades as the field angle increases. We present a technique to estimate the PSF of an adaptive optics telescope as function of the field angle, and use this information in a space-varying image reconstruction technique. Simulated anisoplanatic intensity images of a star field are reconstructed by means of a block-processing method using the predicted local PSF. Two methods for image recovery are used: matrix inversion with Tikhonov regularization, and the Lucy-Richardson algorithm. Image reconstruction results obtained using the space-varying predicted PSF are compared to space invariant deconvolution results obtained using the on-axis PSF. The anisoplanatic reconstruction technique using the predicted PSF provides a significant improvement of the mean squared error between the reconstructed image and the object compared to the deconvolution performed using the on-axis PSF.     

Myopic deconvolution of adaptive optics images by use of object and point-spread function power spectra: reply to comment

Partial correction in adaptive optics (AO) is well understood now. This partial correction is due to the limitations of the AO system performance, which leaves residual phase fluctuations in the instrument pupil. Knowledge of these residuals allows the optical transfer function (OTF) of the high-angular-resolution imaging system to be estimated accurately. Therefore, light scattering by aerosols cannot be invoked to justify the shape of an AO partial-correction OTF in astronomical conditions. The light scattering does not modify the high-angular-resolution OTF but merely contributes to a slight increase of the sky background.     

Volume-consumption comparisons of free-space and guided-wave optical interconnections

We compare volume-consumption characteristics of free-space and guided-wave optical interconnections. System volume consumption is used as a fundamental measure of various point-to-point space-invariant and space-variant interconnections of two-dimensional arrays of N(1/2) x N(1/2) points. We show that, in free-space and space-invariant situations, although volume consumption for macroaperture optics is O(1)(N(3/2)), where O denotes the order, it is only O(2)(N) for microaperture optics. For free-space and space-variant operations only microaperture optics is possible without fundamental power losses. The corresponding minimum volume consumption is O(3)(N(3)). We show that single microaperture-per-channel implementations of either space-invariant or space-variant operations are, in general, more volume efficient than are their two-cascade microaperture-per-channel counterparts. We also show that, for minimizing volume consumption, the optimum relative apertures F#(opt) for space-variant optical elements are, respectively, (5N)(1/2)/4 for a single microaperture-per-channel geometry and (5N)(1/2)/2 for a two-cascade microaperture-per-channel geometry. In guided-wave or fiber interconnect cases our study shows that the volume consumption for space-invariant and space-variant operations is O(4)(N), with O(4) < O(2), and O(5)(N(3/2)), respectively. Thus an important conclusion of the study is that free-space optics is less volume efficient than is guided-wave optics in both space-invariant and space-variant interconnect applications.     

基于坐标变换法的红外成像模型

针对气动光学传输效应,本丈提出一种用坐标旋转法追迹空间任意若干条光线得到光学传递函数(OTF)来计算成像的模型.该方法根据几何光学成像和坐标旋转变换原理,采用基于计算流体力学(CFD)网格的超高声速流场密度数据建立了成像模型,模拟出了流场的降晰效应,并且对仿真结果进行了对比分析.实验结果表明,该模型在一定的精度内反映了现有的气动光学降晰现象.最后探讨了模型的精度及工程应用的意义.     

Restoration of images captured by a staggered time delay and integration camera in the presence of mechanical vibrations

Staggered time delay and integration (TDI) scanning image acquisition systems are usually employed in low signal-to-noise situations such as thermal imaging. Analysis and restoration of images acquired by thermal staggered TDI sensors in the presence of mechanical vibrations that may cause space-variant image distortions (severe geometric warps and blur) are studied. The relative motion at each location in the degraded image is identified from the image when a differential technique is used. This information is then used to reconstruct the image by a technique of projection onto convex sets. The main novelty is the implementation of such methods to scanned images (columnwise). Restorations are performed with simulated and real mechanically degraded thermal images.     

Depth Transfer by an Imaging System

In many applications such as three-dimensional (3-D) data acquisition, the scanning of 3-D objects or 3-D display, it is necessary to understand how an imaging system can be used to obtain information on the structure of an object in the direction perpendicular to the image plane, i.e. depth information. In certain cases the formation of a 3-D image can be described by a theory based on optical transfer functions (OTF): the image intensity distribution is given by the 3-D convolution of the object and a 3-D point spread function (PSF); equivalently, in 3-D Fourier space the image spectrum is the product of the object spectrum and a 3-D OTF. This paper investigates the 3-D PSFs and OTFs that are associated with different pupil functions of the imaging system.     

Application of the Hotelling and ideal observers to detection and localization of exoplanets

The ideal linear discriminant or Hotelling observer is widely used for detection tasks and image-quality assessment in medical imaging, but it has had little application in other imaging fields. We apply it to detection of planets outside of our solar system with long-exposure images obtained from ground-based or space-based telescopes. The statistical limitations in this problem include Poisson noise arising mainly from the host star, electronic noise in the image detector, randomness or uncertainty in the point-spread function (PSF) of the telescope, and possibly a random background. PSF randomness is reduced but not eliminated by the use of adaptive optics. We concentrate here on the effects of Poisson and electronic noise, but we also show how to extend the calculation to include a random PSF. For the case where the PSF is known exactly, we compare the Hotelling observer to other observers commonly used for planet detection; comparison is based on receiver operating characteristic (ROC) and localization ROC (LROC) curves.     

Iterative statistical approach to blind image deconvolution

Image deblurring has long been modeled as a deconvolution problem. In the literature, the point-spread function (PSF) is often assumed to be known exactly. However, in practical situations such as image acquisition in cameras, we may have incomplete knowledge of the PSF. This deblurring problem is referred to as blind deconvolution. We employ a statistical point of view of the data and use a modified maximum a posteriori approach to identify the most probable object and blur given the observed image. To facilitate computation we use an iterative method, which is an extension of the traditional expectation-maximization method, instead of direct optimization. We derive separate formulas for the updates of the estimates in each iteration to enhance the deconvolution results, which are based on the specific nature of our a priori knowledge available about the object and the blur.     

Trajectories in parallel optics

In our previous work we showed the ability to improve the optical system's matrix condition by optical design, thereby improving its robustness to noise. It was shown that by using singular value decomposition, a target point-spread function (PSF) matrix can be defined for an auxiliary optical system, which works parallel to the original system to achieve such an improvement. In this paper, after briefly introducing the all optics implementation of the auxiliary system, we show a method to decompose the target PSF matrix. This is done through a series of shifted responses of auxiliary optics (named trajectories), where a complicated hardware filter is replaced by postprocessing. This process manipulates the pixel confined PSF response of simple auxiliary optics, which in turn creates an auxiliary system with the required PSF matrix. This method is simulated on two space variant systems and reduces their system condition number from 18,598 to 197 and from 87,640 to 5.75, respectively. We perform a study of the latter result and show significant improvement in image restoration performance, in comparison to a system without auxiliary optics and to other previously suggested hybrid solutions. Image restoration results show that in a range of low signal-to-noise ratio values, the trajectories method gives a significant advantage over alternative approaches. A third space invariant study case is explored only briefly, and we present a significant improvement in the matrix condition number from 1.9160e+013 to 34,526.     

运动模糊不变量研究

图像的运动模糊是摄像机在曝光期间与场景间相对运动而造成的图像退化,但现有算法对运动模糊的恢复精度有限.本文分析了图像运动模糊的退化模型,提出了运动模糊不变量的概念,证明了图像零阶矩、第一个Hu不变矩和SIFT为运动模糊不变量,并给出了测试和应用.结果表明运动模糊不变量是存在的,而且可以用于不确定性运动模糊图像的匹配和识别领域.     

Anisoplanatic deconvolution of adaptive optics images

A modified method for maximum-likelihood deconvolution of astronomical adaptive optics images is presented. By parametrizing the anisoplanatic character of the point-spread function (PSF), a simultaneous optimization of the spatially variant PSF and the deconvolved image can be performed. In the ideal case of perfect information, it is shown that the algorithm is able to perfectly cancel the adverse effects of anisoplanatism down to the level of numerical precision. Exploring two different modes of deconvolution (using object bases of pixel values or stellar field parameters), we then quantify the performance of the algorithm in the presence of Poissonian noise for crowded and noncrowded stellar fields.     

高斯型点扩展函数估计的最近邻算法

本文针对计算光学切片中的最近邻算法提出了一种改进算法.通过小波变换计算出高斯点扩展函数的方差值,再根据相邻图像成像及高斯函数特性,得出所需的高斯型层间点扩展函数.同时,文章还给出了两种高斯型层间点扩展函数方差的获得方式及获得过程,对最近邻算法中的加权因子的取值范围做出了讨论,对传统的最近邻算法做出了改进.实验表明,本算法能够更有效地复原符合最近邻要求的切片图像.在点扩展函数未知的情况下,复原效果要优于传统方法.     

Upscaling image resolution of compact imaging systems using wavefront coding and a property of the point-spread function

We propose an image-resolution upscaling method for compact imaging systems. The image resolution is calculated using the resolving power of the optics and the pixel size of a digital image sensor. The resolution limit of the compact imaging system comes from its size and the number of allowed lenses. To upscale the image resolution but maintain the small size, we apply wavefront coding and image restoration. Conventional image restoration could not enhance the image resolution of the sensor. Here, we use the upscaled image of a wavefront-coded optical system and apply an image-restoration algorithm using a more precisely calculated point-spread function (PSF) as the deconvolution filter. An example of a wavefront-coded optical system with a 5-megapixel image sensor is given. The final image had a resolution equivalent to that of a 10-megapixel image using only four plastic lenses. Moreover, image degradation caused by hand motion could also be reduced using the proposed method.     

Defocus transfer function for circularly symmetric pupils

We present a two-dimensional function that graphically illustrates the effects of defocus on the optical transfer function (OTF) associated with a circularly symmetric pupil function. We call it the defocus transfer function (DTF). The function is similar in application to the ambiguity function, which can be used to display the OTF associated with a defocused rectangularly separable pupil function. The properties of the DTF make it useful for analyzing optical systems with circularly symmetric pupils when one is interested in the OTF as a function of defocus. In addition to presenting these properties, we give examples of the DTF for systems with clear, bifocal, and annular pupil functions.     

MISTRAL: a myopic edge-preserving image restoration method, with application to astronomical adaptive-optics-corrected long-exposure images

Deconvolution is a necessary tool for the exploitation of a number of imaging instruments. We describe a deconvolution method developed in a Bayesian framework in the context of imaging through turbulence with adaptive optics. This method uses a noise model that accounts for both photonic and detector noises. It additionally contains a regularization term that is appropriate for objects that are a mix of sharp edges and smooth areas. Finally, it reckons with an imperfect knowledge of the point-spread function (PSF) by estimating the PSF jointly with the object under soft constraints rather than blindly (i.e., without constraints). These constraints are designed to embody our knowledge of the PSF. The implementation of this method is called MISTRAL. It is validated by simulations, and its effectiveness is illustrated by deconvolution results on experimental data taken on various adaptive optics systems and telescopes. Some of these deconvolutions have already been used to derive published astrophysical interpretations.     

Design methods for space-variant optical interconnections to achieve optimum power throughput

Optoelectronic systems based on space-variant optics give great freedom to the system designer in terms of interconnect topologies. One feature of space-variant systems is that they can achieve a high interconnect density. However, this density is achieved by having large arrays of diffractive elements with very small apertures relative to the propagation distances involved. Thus diffraction losses from the finite apertures can significantly affect power throughput for these types of systems, regardless of the diffractive efficiencies of the optical elements involved. Therefore it is desirable that this loss be minimized. We present several space-variant optical interconnect design methods (for both one-to-one and fan-out interconnects) and compare them in terms of power throughput for diffraction-limited interconnect distances. Both numerical simulations and experimental results are presented.