Image deblurring based on ForIcM: Fourier shrinkage and incomplete measurements

Abstract

In this paper, we propose a new deblurring algorithm, which is based on image reconstruction from incomplete measurements in Fourier domain. Our algorithm has two steps. Firstly, an initial estimator is obtained using Fourier regularised inverse operator. Secondly, parts of the estimator’s Fourier coefficients are saved, and the others are removed to suppress noise energy, and then the remaining coefficients are used to recover image based on the sparse constraints. This image reconstruction problem is an optimisation problem which is solved by a fast algorithm named split Bregman iteration. Our algorithm combines two different regularisation strategies efficiently by applying a selection matrix. The tests using images with different blurs and noise produce good results. The experiment shows that our method gives better performance than many other competitive deblurring methods.     

基于反卷积的手机屏下成像图像恢复

随着全面屏手机的发展,手机屏下成像的研究应运而生。但由于手机屏幕存在电路走线和其他不透明部分,光通过屏幕会产生衍射,降低成像结果的图像质量,本文从图像复原的角度,对屏下相机拍摄的图像进行恢复。通过测量得到手机成像系统的点扩散函数(PSF),利用测得的PSF,对图像进行反卷积处理。本文改进了传统的反卷积方法,对原始图像进行颜色空间转换,然后对不同的通道分别处理。相较于传统反卷积方法,改进后的反卷积方法得到的处理结果在结构相似度(SSIM)、峰值信噪比(PSNR)等指标上都有提高,运行时间更短。在分通道反卷积之后,使用非局部平均算法进行去噪处理,进一步提高了屏下图像的质量。     

稀疏先验型的大气湍流退化图像盲复原

图像盲复原是仅从降质图像就恢复出模糊核和真实锐利图像的方法,由于其病态性,通常需要加入图像先验知识约束解的范围。针对传统的图像梯度l2和l1范数先验不能真实刻画自然图像梯度分布的特点,本文将图像梯度稀疏先验应用于单帧大气湍流退化图像盲复原中。先估计模糊核再进行非盲复原,利用分裂Bregman算法求解相应的非凸代价函数。仿真实验表明,与总变分先验(l1范数)相比,稀疏先验有利于模糊核的估计、产生锐利边缘和去除振铃等,降低了模糊核的估计误差从而提高了复原质量。最后对真实湍流退化图像进行了复原。     

Improved TV for blind deblurring with split Bregman iteration

In this paper, an improved TV (total variation) with split Bregman iteration is proposed to improve the result of blind image deblurring. According to the property of the higher partial derivatives in the local image, adaptive values of regularisation parameters in TV algorithm are calculated in order to suppress the ringing artefacts effectively. To alleviate the difficulty of L₁ norm problem, the split Bregman iteration is also adopted. Comparisons are made between the proposed and traditional methods, and experimental results prove that the proposed algorithm is not only robust to different size of blur kernels, but also can suppress the ringing artefacts to a great extent in the latent image, both visually and theoretically.     

Improving closely spaced dim object detection through multiframe blind deconvolution of near stellar neighbourhoods

A new iterative algorithm is proposed to improve the detection of dim stellar objects that are in the neighbourhood of a bright object, using short-exposure images. This method separates data functions into the primary bright object function, the neighbourhood system function, and the background function. This approach uses the principles of the Expectation-Maximization algorithm with the Gerchberg-Saxton phase retrieval algorithm to overcome the image degradation caused by the photon counting noise from the charge-coupled devices and the turbulent atmospheric conditions. The performance of this new neighbourhood system algorithm is compared with that of the multiframe blind deconvolution algorithm, using laboratory data and computer-simulated data. This paper provides an improved technique to image closely spaced dim objects.     

应用编程智能处理不满幅遥感影像

遥感影像分图幅后,会出现不满幅的情况,采用其它影像填充是常用的方法。通过Photoshop编程这一方法智能填充不满幅影像,改变传统处理方法,大大提高工作效率。本文研究了Photoshop对象模型、编程语言,对不满幅影像处理的作业流程和程序实现原理进行了阐述。本文扼要说明主要部分的代码。     

A magnetic resonance image reconstruction method using support of first‐second order variation

This article addresses the problem of reconstructing a magnetic resonance image from highly undersampled data, which frequently arises in accelerated magnetic resonance imaging. We propose to impose sparsity of first and second order difference sparse coefficients within the complement of the known support. Second order variation is involved to overcome blocky effects and support information is used to reduce the sampling rate further. The resulting optimization problem consists of a data fidelity term and first‐second order variation terms penalizing entries within the complement of the known support. The efficient split Bregman algorithm is used to solve the problem. Reconstruction results from magnetic resonance imaging data corresponding to different sampling rates are shown to illustrate the performance of the proposed method. Then, we also assess the tolerance of the new method to noise briefly. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 277–284, 2015     

基于颜色空间变换和CNN的自适应去模糊方法

目的研究数字图像中的去模糊问题,从受损的模糊图像中恢复出清晰图像。方法针对现有图像去模糊算法无法保留图像高频信息及容易产生振铃效应等问题,提出一种基于Y通道反卷积和卷积神经网络的两阶段自适应去模糊算法(SDYCNN)。在第1阶段,将数字图像转换至YUV颜色空间,根据图像无参考质量评价分数与模糊核尺寸之间的对应关系,在Y通道内自适应确定模糊核尺寸并进行反卷积增强;第2阶段将第1阶段中的反卷积增强作为预处理方式,通过4层卷积神经网络建立反卷积增强后的图像与清晰图像之间的映射关系,实现图像去模糊。结果轻微模糊图像在第1阶段便能够得到较好的去模糊效果,严重模糊图像经过第1阶段的反卷积增强,也有助于神经网络中特征的快速提取。结论实验结果表明,该算法不仅对于模糊图像具有良好的恢复效果,运算效率也有显著提升。     

Thermal imidization optimization of polyimide thin films using Fourier transform infrared spectroscopy and electrical measurements

The influence of the imidization temperature on the molecular structure and on the thermal and electrical properties of polyimide thin films is investigated. The effects of the imidization temperature on the formation of the imide rings are studied by Fourier transform infrared (FTIR) spectroscopy through the changes of the extent of imidization. However, the determination of the optimal imidization temperature shows a poor accuracy through this technique. Therefore, the quantification of several electrical properties used as probes of the imidization reaction advancement (particularly high field electrical measurements) allows obtaining a highest accuracy of the optimal imidization temperature. An optimum temperature is found at 400 °C while desimidization is observed at 450 °C. This is in good agreement with FTIR results.     

Structural damage diagnosis using incomplete static responses and LS-SVM

This paper presents novel approach to structural damage detection and estimation using incomplete static responses of a damaged structure and least squares support vector machine (LS-SVM). The presented method is based on the reduced stiffness matrix to formulate incomplete static responses as input parameters to the LS-SVM. The presented method is applied to a plane steel bridge, a four-span continuous beam and four-storey plane frame containing several damages. Also, the effect of the discrepancy in stiffness between the finite element model and the actual tested system has been investigated. The results show that the presented method is sensitive to the location and severity of the structural damage in spite of the incomplete noisy data and modelling errors.     

Fast Algorithms for the Anisotropic LLT Model in Image Denoising

In this paper, we propose a new projection method for solving a general minimization problems with two $L^1$-regularization terms for image denoising. It is related to the split Bregman method, but it avoids solving PDEs in the iteration. We employ the fast iterative shrinkage-thresholding algorithm (FISTA) to speed up the proposed method to a convergence rate $O$($k^-$$^2$). We also show the convergence of the algorithms. Finally, we apply the methods to the anisotropic Lysaker, Lundervold and Tai (LLT) model and demonstrate their efficiency.     

泊松噪声下图像去模糊的几个非凸模型

图像复原中通常假设图像在梯度域上是稀疏的,而非凸正则化方法会更加促进稀疏性。本文基于近年出现的几类非凸正则项,提出了泊松噪声下图像去模糊问题的几个非凸模型,发展了相应的高效求解算法,并研究了算法的收敛性;数值实验表明所提出的非凸模型可以增强图像在梯度域上的稀疏性,并优于一些现有的方法。     

Cost-effective and high-resolution wavelength interrogation unit using an incomplete asymmetric arrayed waveguide grating

This paper presents a wavelength interrogation unit using an incomplete asymmetric arrayed waveguide grating (AWG) without output waveguides. The incomplete asymmetric AWG converts the wavelengths of the incident light into a spatial intensity distribution. The center of the spatial distribution is determined by a one-dimensional position sensitive detector (PSD). The simulation results show that wavelength shifts can be precisely interrogated by the device with a wavelength resolution of 3.5 pm. The device can be applied to the interrogation of fiber Bragg grating (FBG) temperature sensors with the temperature resolution of 0.3°C.     

随机振幅-相位编码虚拟光学加密系统

通过对双随机相位编码光学加密系统中空域的随机相位模板进行置换,提出采用随机振幅-相位模板对图像进行加密的新方法。理论分析表明,当随机振幅板为零均值白噪声且与频域相位板统计独立时,被加密图像的自相关函数为二维冲击函数,表明原始图像被加密为平稳的复随机白噪声,因而可以抵御盲反卷积攻击。采用计算机进行模拟,证实了所提方法的有效性。最后讨论了该方法相对于双随机相位编码系统的优越性:对空域密钥的统计学要求更低、在频域密钥泄露情况下系统鲁棒性更强。但是,由于物理上不存在幅度为负值的光波,因此该系统只能使用数字虚拟的方法来实现。     

Obtaining more accurate resistance measurements using the six-wire ohms measurement technique

During production of resistors and resistive devices, one of the most troublesome problems for manufacturers involves increased measurement errors caused by adjacent resistive elements and contamination. Both of these effects lead to poor yields, low productivity and subsequently lower profitability. This paper describes both effects and discusses the six-wire ohms measurement technique as a means of compensating for the problems. In addition, some of the most common limitations of the six-wire ohms measurement technique will be discussed. At the end, some practical examples will demonstrate the usage of available test and measurement equipment in production. Major trade-offs between accuracy and speed while testing radial resistors and resistor networks will be shown. © 1998 John Wiley & Sons, Ltd.     

基于四元数傅里叶变换的彩色图像数字水印算法

目的提高彩色图像数字水印的抗攻击性能,包括缩放、旋转、平移、噪声攻击等。方法基于坐标变换和四元数傅里叶变换提出一种彩色图像数字水印算法。介绍彩色图像四元数表示形式及其双侧傅里叶变换,并分析笛卡尔坐标和极对数坐标之间的变换关系。选择四元数傅里叶变换后实部的中低频部分作为嵌入区域;为提高算法的抗几何攻击能力,给出笛卡尔坐标系和对数极坐标系之间对应点的位置关系;详细论述水印嵌入和提取的流程。结果针对噪声、滤波、剪切等攻击进行了实验研究,结果表明所述算法可以提高提取信息的准确率和水印的抗攻击能力。结论该算法在保证水印隐蔽性的同时能够抵抗一定程度的攻击,满足版权保护和数字防伪的需要。     

利用灰度图提高Fourier变换轮廓术的测量精度

在ＦＴＰ测量中,常利用π相移方法来消除零频,以避免谱频混叠,提高ＦＴＰ的测量精度。此时,测量系统中包含相移装置,增加了系统的复杂性。然而,人们常常忽略了灰度图中包含的信息在ＦＴＰ测量中的作用。本文提出了在ＦＴＰ测量中利用一帧灰度图来提高测量精度的方法,该方法测量装置简单,又可以达到π相移的效果,在实际的ＦＴＰ测量中的意义。     

基于傅里叶卷积和多特征调制的图像修复网络

目的 解决大面积破损难以修复且修复过程中感受野、特征空间信息利用不足,导致修复后的孔洞区域与背景之间出现结构、纹理、风格不一致的问题。方法 基于傅里叶卷积和多特征调制的修复网络FFC-MFMGAN,傅里叶卷积在网络的浅层便具有较大的感受野,尤其是在宽掩码时能够跳过掩码区域,捕获到有效特征,多特征调制生成网络能够分别利用完整区域的信息和随机样式操纵,增强与未受损区域的语义连贯性,以及大空洞率下修复的多样性。结果 在Place 2数据集上,将文中方法与其他图像修复方法进行了对比实验,经过测试,各类指标均得到明显改善,峰值信噪比提高了1.4%,结构相似性提高了4.5%,平均绝对误差降低了12.6%,基于学习的感知图像块相似性降低了9.1%。结论 FFC-MFMGAN网络能够较好地修复大面积不规则孔洞,同时增强修复图像的全局结构性和清晰度,对实际包装印刷图像的缺陷修复也有一定参考价值。     

Image deblurring using empirical Wiener filter in the curvelet domain and joint non-local means filter in the spatial domain

In this paper, an efficient image deblurring algorithm is proposed. This algorithm restores the blurred image by incorporating a curvelet-based empirical Wiener filter with a spatial-based joint non-local means filter. Curvelets provide a multidirectional and multiscale decomposition that has been mathematically shown to represent distributed discontinuities such as edges better than traditional wavelets. Our method restores the image in the frequency domain to obtain a noisy result with minimal loss of image components, followed by an empirical Wiener filter in the curvelet domain to attenuate the leaked noise. Although the curvelet-based methods are efficient in edge-preserving image denoising, they are prone to producing edge ringing which relates to the structure of the underlying curvelet. In order to reduce the ringing, we develop an efficient joint non-local means filter by using the curvelet deblurring result. This filter could suppress the leaked noise while preserving image details. We compare our deblurring algorithm with a few competitive deblurring techniques in terms of improvement in signal-to-noise-ratio (ISNR) and visual quality.