Image deconvolution using incomplete Fourier measurements

In this article, we propose a new deconvolution algorithm, which is based on image reconstruction from incomplete measurements in Fourier domain. Our algorithm has two steps. First, an initial estimator is obtained using Fourier regularized inverse operator. Second, parts of the estimator's Fourier coefficients are saved, and the others are removed to suppress noise energy, then the remaining coefficients are used to recover image based on the sparse constraints. This image reconstruction problem is an optimization problem that is solved by a fast algorithm named split Bregman iteration. Different from other deconvolution algorithms, our algorithm only uses parts of Fourier components to restore the blurred image and combines two different regularization strategies efficiently by applying a selection matrix. The experiment shows that our method gives better performance than many other competitive deconvolution methods. © 2012 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 22, 233–240, 2012     

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。     

Defocus deblurring for catadioptric omnidirectional imaging based on spatially invariant point spread function

The problem of catadioptric omnidirectional imaging defocus blur, which is caused by lens aperture and mirror curvature, becomes more severe when high resolution sensors and large apertures are applied. In order to overcome this problem, a novel method based on computational photography is proposed. Firstly, the defocus blur of catadioptric omnidirectional imaging is analyzed to calculate the point spread function for different scene points. Then, the defocus blur kernel of omnidirectional image is confirmed to be spatially invariant when rotating the focus ring of camera lens during an image’s integration time. Lastly, the deconvolution algorithm using prior sparse derivatives is applied to obtain all-focused/sharp omnidirectional images. Experimental results demonstrate that the proposed method is effective for omnidirectional image deblurring and can be applied to most existing catadioptric omnidirectional imaging systems.     

A robust incomplete factorization based on value and space constraints

This paper describes an incomplete factorization method for computing a preconditioning matrix for the conjugate gradient method. The incomplete factorization satisfies the stability requirement that the incomplete factor remains positive definite throughout the factorization. When selecting a preconditioner for the conjugate gradient method, the number of non-zero entries to be retained in the incomplete factor should be limited so that the amount of computations involving the preconditioning matrix is minimized. This paper introduces a method to generate an effective preconditioning matrix within a predefined space. Numerical results are presented to demonstrate the effectiveness of the incomplete factor as a preconditioner for the conjugate gradient method for solving large-scale structural engineering problems.     

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。     

基于点扩散函数的散焦图像复原及其效果比较

针对已知的散焦图像数学模型,通过先估计点扩散函数(PSF),然后利用维纳滤波估计原始清晰图像的方法,探讨PSF、调制传递函数(MTF)的估计方法,具体包括边缘地物法、空间频率响应法、基于APEX方法的估计算法.结合复原图像的模糊度客观评价函数和主观视觉评价来判别各方法的优劣,结果表明:边缘地物法较优.     

基于PMP的钢轨三维形貌在线测量模糊条纹复原

在线相位测量轮廓术(PMP)中,当被测物体运动速度较高时,所采集的变形条纹往往为运动模糊图像,使得复原误差增大,严重时可能导致三维重建无法进行。将在线PMP运用于钢轨外形及表面缺陷的在线三维测量时,为了实现钢轨表面模糊变形条纹的清晰化,本文对维纳滤波法、点扩散函数算法、盲解卷积算法和Richardson-Lucy算法等几种模糊图像复原算法进行了对比分析,用峰值信噪比对模糊条纹图像的复原效果进行评估。同时,研究了车辆运行速度和图像复原效果之间的关系,得出了复原效果与运行速度之间的关系曲线,进行了误差分析,并用在线PMP实现了钢轨外形的三维重建。理论及实验结果表明：在对钢轨外形轮廓及表面缺陷的在线三维测量时,Richardson-Lucy算法的复原效果最佳,图像复原程度与车辆运行速度呈多项式关系。     

最大相关峭度解卷积结合稀疏编码收缩的齿轮微弱故障特征提取

针对强背景噪声环境下齿轮早期故障诊断问题,提出了最大相关峭度解卷积结合稀疏编码收缩的微弱故障特征提取方法。由于最大相关峭度解卷积算法的处理结果同时受滤波器长度参数及解卷积周期参数的影响,为自适应地实现最佳的解卷积效果,利用粒子群算法优良的寻优特性,对最大相关峭度解卷积算法的最佳影响参数组合进行搜索。原故障信号经影响参数优化的最大相关峭度解卷积算法处理后,冲击特征会明显增强,为剔除剩余噪声,对所获解卷积信号做进一步稀疏编码收缩降噪处理,并通过分析降噪信号的包络谱来识别故障特征频率成分。实例分析结果验证了该方法的有效性和可靠性。     

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。     

基于最小二乘准则的模糊估计和图像复原

在计算光学显微成像技术中,点扩展函数往往是未知的,且不易获取,从而给图像复原带来很大困难。基于最小二乘准则和最优化理论,提出了利用变尺度法的三维点扩展函数参数估计算法;针对传统EM算法存在复原效果细节丢失严重等问题,提出最小二乘共轭梯度三维图像复原算法。算法在点扩展函数参数估计和求解真实图像之间进行交替迭代,从而得到图像的最优估计。实验表明,新算法在较短时间内,能够较准确地估计出点扩展函数参数,并得到较好的复原结果。     

基于三角形几何相似性的图像配准与拼接

介绍了一种基于三角形几何相似性的图像配准方法.提取两幅待拼接图像的特征点,将每幅图像各自的重叠区域内或图像内容复杂情况下的选定区域内的特征点任意组合为三角形,得到分别对应于每一幅图像的三角形集合.然后根据定义的新的三角形表示方法,包括最大角方向和最小角方向,在两组三角形集合内层层筛选任意组合的三角形对,最终找到其中的匹配三角形对,即相似三角形对,从而找到匹配的点对.最后计算图像间变换矩阵,对图像进行拼接,得到了一张具有更宽视野的无缝拼接图.该方法只与特征点间相互几何位置有关,所以对两幅图像间的灰度差异、任意的旋转、缩放等都表现了很强的鲁棒性.     

基于聚类和协同表示的超分辨率重建

图像超分辨率重建是利用单幅或多幅降质的低分辨率图像重建得到高分辨率图像,以提高图像的视觉效果并获得更多可用的信息。本文提出结合图像特征聚类和协同表示的超分辨率重建方法。在训练阶段根据图像的特征信息对图像样本进行聚类并利用图像特征的差异性训练不同的字典,克服了传统训练单个字典方法对图像特征表示不足的缺点。而且利用协同表示方法求得不同聚类的高、低分辨率图像样本之间的映射矩阵,提高了图像重建速度。实验表明,本文方法与其他方法相比,不仅提高了重建图像的PSNR和SSIM指标,而且改善了视觉效果。     

Fatigue assessment and fatigue life calculation of quenched and tempered SAE 4140 steel based on stress–strain hysteresis, temperature and electrical resistance measurements

In this paper, mechanical stress–strain-hysteresis, temperature and electrical resistance measurements are performed for the detailed characterization of the fatigue behaviour of quenched and tempered SAE 4140 steel used for many applications in the automotive industry. Stress-controlled load increase and constant amplitude tests (CATs) were carried out at ambient temperature on servo-hydraulic testing systems. The applied measurement methods depend on deformation-induced changes of the microstructure in the bulk material and represent the actual fatigue state. The plastic strain amplitude, the change in temperature and the change in electrical resistance can be equally used for an assessment of baseline fatigue properties in generalized cyclic deformation curves as well as in generalized Morrow and Coffin–Manson curves. On the basis of comprehensive experimental fatigue data, the physically based fatigue life calculation method ‘PHYBAL’ based on the generalized Basquin equation was developed. S–N (Woehler) curves calculated with ‘PHYBAL’ using data from only three fatigue tests agree very well with the conventionally determined ones.     

Image fusion based on wavelet transform and gray-level features

Image fusion makes the fused image more reliable and intelligible, and more suitable for human vision and computer detection, classification, recognition and understanding. This paper proposes a pixel-level image fusion method for merging two source images of the same scene using wavelet transform and gray-level features (GLF). First, a three-level discrete two-dimensional wavelet transform is used to decompose the two source images into low-frequency image components and horizontal, vertical, and diagonal high-frequency components. Then, the spatial frequency correlation coefficient is used to determine the pixel fusion rule to apply to each of the low-frequency images, and the correlation coefficient of the GLF is used to determine the pixel fusion rule to apply to each of the high-frequency images. Finally, the fused image is reconstructed using inverse wavelet transform. The results of the experiments conducted indicate that the proposed method is more effective than relevant conventional methods.     

分水岭变换和统计区域合并的图像分割算法研究

提出了一种基于分水岭变换和统计区域合并的图像分割方法.该方法综合利用高斯低通滤波、分水岭变换和统计区域合并,先对原始图像提取分割标记,然后利用Meyer分水岭变换对标记分水岭进行分割,最后利用概率统计的方法对过分割区域进行合并.该算法通过调节尺度参数可以实现由粗到细(coarse-to-fine)的分割.实验结果表明,这种简单可行的算法在分割噪声图像时依然有良好的效果,具有较强的鲁棒性.     

Optical image encryption based on compressive sensing and chaos in the fractional Fourier domain

We propose a novel image encryption algorithm based on compressive sensing (CS) and chaos in the fractional Fourier domain. The original image is dimensionality reduction measured using CS. The measured values are then encrypted using chaotic-based double-random-phase encoding technique in the fractional Fourier transform domain. The measurement matrix and the random-phase masks used in the encryption process are formed from pseudo-random sequences generated by the chaotic map. In this proposed algorithm, the final result is compressed and encrypted. The proposed cryptosystem decreases the volume of data to be transmitted and simplifies the keys for distribution simultaneously. Numerical experiments verify the validity and security of the proposed algorithm.     

Image encoding based on a damped triangular function and a discrete sequence

An encoding system based on a damped triangular function is presented. The image encoding is implemented by a computational algorithm, which transforms the image intensity to a triangular function. This procedure generates a random pattern from the original image. Thus, a secret image is obtained to perform the electronic transmission. The decoding algorithm is implemented by an inverse discrete damped triangular function. This procedure generates a discrete sequence by sampling the damped triangular function. The sequence contains the key data to compute the image decoding. Then, the original image is retrieved by matching the intensity of the secret image in the discrete sequence. The viability of the proposed method is established based on the quality of the image encoding and decoding. These parameters are evaluated based on traditional encoding methods to provide evidence of the power of the proposed method. Thus, the contribution of the proposed technique in the field of image encoding is stated. The technique is tested by encoding real objects and its results are presented in computational form.     

Image segmentation model based on adaptive adjustment of global and local information

In this article, an adaptive mixture model for image segmentation that synthesizes both global information and local information using a new adaptive balance function has been proposed. Given the variety of possible image characteristics that may have to be processed, the proposed model can adaptively adjust the weighting to drive curve evolution trends and states. In this way, the intensity information of weak boundaries and complex backgrounds can be extracted more precisely, thus enabling the model to produce better results for low‐contrast images and complex structures. In addition, a Gaussian filtering process has been added to the model to smooth and standardize the level set function, and a parameter has been introduced to speed up the curve evolution. A penalty term is also used to eliminate the need for complex re‐initialization procedures. Experimental results for various kinds of images efficiently demonstrate the good performance of the proposed model in terms of both speed and accuracy. © 2016 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 26, 179–187, 2016     

Image encryption based on a reality-preserving fractional discrete cosine transform and a chaos-based generating sequence

A novel image encryption technique based on a reality-preserving fractional discrete cosine transform (FrDCT) and a chaos-based generating sequence is proposed. The FrDCT is a generalization of the discrete cosine transform (DCT). This reality-preserving FrDCT inherits the virtues of both the DCT and fractional transform, providing improved security and flexibility by employing the generating sequence as an extra key in addition to the fractional orders. The most fascinating advantage of the FrDCT is its reality-preserving property, which ensures real ciphertext for real plaintext, which is conducive to display, storage, and transmission. Performance and security analysis demonstrates that this algorithm is valid, secure, sensitive to keys, and robust to noise and occlusion attacks.     

基于线性变换与多种平滑去噪的爆堆图像增强方法

介绍了自主设计的"基于灰度线性变换与综合多种平滑去噪"的爆堆图像增强方法。首先根据爆堆图像的灰度分布情况对爆堆图像进行灰度线性变换,使图像中矿岩与背景区别更加明显;然后对爆堆图像用均值滤波、中值滤波、高斯滤波进行综合平滑处理,这样不仅祛除了图像的噪声,而且很好的保留了图像中矿岩的边缘。