Non-chaotic and chaotic propagation of stationary and dynamic images through MVKS turbulence

Anisoplanatic electromagnetic (EM) propagation across a turbulent atmosphere has been recently examined for an unmodulated carrier propagating over an image-bearing transparency through optical lensing, and for the embedded information inside a carrier recovered using heterodyning and digital demodulation. Carrier modulation yielded better recovery than simple lens-based imaging. A possible mitigation strategy is proposed whereby the image information is encrypted on an RF chaotic carrier, thereafter secondarily embedded onto an optical carrier. Results based on the modified von Karman (MVKS) and the Hufnagel-Valley (H-V) models showed that the signal/image recovery under turbulence is improved compared with non-chaotic propagation. The case of time-varying/dynamic images is also taken up; it is demonstrated via cross-correlation products that turbulence is mitigated by the use of chaotic carrier encryption. Overall, transmission via chaos offers mitigation against distortions due to turbulence along with the security feature inherent via the chaos keys which prevent signal recovery without key-matching.     

Road Extraction from High Resolution Remote Sensing Image based on Shape Analysis with Gestalt Theory

Simulating the psychological experience of human vision，a road extraction model based on the format tower is proposed to extract the road in the high resolution remote sensing image from the perspective of morphology.Firstly，based on the spectral and texture information，the suspected road targets are extracted by using segmentation technology.Then these targets are classified according to their reliability and extract the road targets for each category.Finally，three types of identified road information are verified and merged，and the continuous smooth road extraction results are obtained.Experiments on real high resolution images show that the results are consistent with the visual perception of the human eye，and the overall classification accuracy is higher，indicating that the algorithm is effective and feasible and has good use value.     

基于颜色四通道及空间金字塔的鱼类图像检索

随着计算机视觉技术在海洋水产领域中的应用不断加深，鱼类图像检索在渔业资源调查、鱼类行为学分析等方面发挥了巨大的作用。通过研究发现，鱼类图像的背景信息会对鱼类图像检索造成极大干扰，而且鱼类图像中颜色、纹理、形状等特征由于空间位置信息的缺乏而使检索的准确率不高。为解决以上问题，提出了一种新的基于颜色四通道及空间金字塔的鱼类图像检索算法。首先，提取视觉显著性图将鱼类图像的前景和背景分开，从而减少图像背景对检索的干扰；其次，为了使图像特征包含一定的空间位置信息，利用空间金字塔的理论对图像进行分割，在此基础上，将图像转为HSVG四通道图并提取SURF特征；；最后，得到检索结果。为验证所提算法的有效性，在QUT_fish_data数据集和DLOU_fish_data数据集上对算法的查全率、查准率与经典的HSVG算法和显著性分块算法进行对比：在两个数据集上查准率分别比传统的HSVG算法最多分别提高12%和5%，查全率最多分别提高7%和22%；比传统的显著性分块算法查准率最多分别提高15%和5%，查全率最多分别提高36%和22%；从而证明所提算法是有效的，能有效提升鱼类图像的检索效果。     

Sparse non-convex Lp regularization for cone-beam X-ray luminescence computed tomography

Cone-beam X-ray luminescence computed tomography (CB-XLCT) is an attractive hybrid imaging modality, and it has the potential of monitoring the metabolic processes of nanophosphors-based drugs in vivo. However, the XLCT imaging suffers from a severe ill-posed problem. In this work, a sparse nonconvex L_p (0?p?L₁ regularization. Further, an iteratively reweighted split augmented lagrangian shrinkage algorithm (IRW_SALSA-L_p) was proposed to efficiently solve the non-convex L_p (0?p?p-values (1/16, 1/8, 1/4, 3/8, 1/2, 5/8, 3/4, 7/8) in both 3D digital mouse experiments and in vivo experiments. The results demonstrate that the proposed non-convex methods outperform L₂ and L₁ regularization in accurately recovering sparse targets in CB-XLCT. And among all the non-convex p-values, our L_p(1/4?p?相似文献   

Assessment of local strain field in adhesive layer of an unsymmetrically repaired CFRP panel using digital image correlation

The present study focuses on experimental investigation of through the thickness displacement and strain field in thin adhesive layer in single sided (unsymmetrical) patch repaired CFRP (carbon fiber reinforced polymer) panel under tensile load. Digital image correlation (DIC) technique is employed to acquire the displacement and strain (longitudinal, peel and shear) field. Experimental determination of shear transfer length based on shear strain field obtained from DIC is introduced to estimate the optimum overlap length which is an essential parameter in patch design for the repair of CFRP structures. Further, DIC experiment with magnified optics is performed to get an insight into complex and localized strain field over thin adhesive layer especially at critical zones leading to damage initiation. The failure mechanism, load displacement behavior, damage initiation and propagation are closely monitored using DIC. The influence of patch edge tapering on strain distribution in adhesive layer is also investigated. The DIC successfully captures the global and localized strain field at critical zones over thin adhesive layer and further helps in monitoring the damage based on strain anomalies. Strains are found to have maximum magnitude at the patch overlap edge and the shear strain level in adhesive layer is higher than the peel strain. Normal tapering increases the peel strain and has negligible influence on shear strain level in adhesive layer. The recommended overlap length is found to be consistent with the recommendation in the literature. Whole field strain pattern and the overlap length obtained from experiment are further compared with the finite element analysis results and they appear to be in good coherence.     

因素空间理论下基点分类算法研究

目前，基于因素空间理论的背景基提取算法计算过程复杂，初始化必须依赖各因素极值，基点数量提取冗余等原因，未能在应用中取得很好效果。为此，结合内点判别法和知识可继承、可扩展的思想，提出一种计算简单、初始化独立、基点数量小的改进的背景基提取算法。然后，利用改进的背景基提取算法构造出一种全新的数据分类算法-基点分类算法，基点分类算法以提取每一类样本的背景基为预测模型，再通过新定义的λ-背景基，优化预测模型。数值实验表明:基点分类算法原理简单、构造难度小、分类模型泛化能力强，预测能力准确率高，同时严格的模型限定区域又能为识别新类别提供新方法。     

一类两性分枝过程条件均值增长率的极限性质

本文主要研究随机环境中配对依赖人口数两性 Galton-Watson 分枝过程的条件均值增长率的极限性质．利用上可加函数的性质，得到配对单元平均增长率的极限性质和该过程条件均值的上界和下界．文中给出了关于过程条件均值增长率的两个序列，利用配对单元平均增长率的性质，获得了这两个序列的极限性质．随机环境中配对依赖人口数两性分枝过程比较复杂，本文的结论推广了现有的研究成果．     

Image Super-Resolution Based on Generative Adversarial Networks: A Brief Review

Single image super resolution (SISR) is an important research content in the field of computer vision and image processing. With the rapid development of deep neural networks, different image super-resolution models have emerged. Compared to some traditional SISR methods, deep learning-based methods can complete the superresolution tasks through a single image. In addition, compared with the SISR methods using traditional convolutional neural networks, SISR based on generative adversarial networks (GAN) has achieved the most advanced visual performance. In this review, we first explore the challenges faced by SISR and introduce some common datasets and evaluation metrics. Then, we review the improved network structures and loss functions of GAN-based perceptual SISR. Subsequently, the advantages and disadvantages of different networks are analyzed by multiple comparative experiments. Finally, we summarize the paper and look forward to the future development trends of GAN-based perceptual SISR.     

主/次显示器视距设计对头部关节舒适度的影响

以视平线可与显示器中心重合为准,分别探讨显示器中心在视平线上方、下方时不同视距对头部关节舒适度的影响. 实验自变量为视距(眼睛与显示器中心的水平距离),因变量为头部关节舒适度. 实验结果显示:1)显示器中心在人视平线上方时,头部舒适性状态始终处于不舒适状态,此时视距与人的头部舒适性关系成正比,即视距越大,头部舒适性越好;2)显示器中心在人视平线下方时,头部关节舒适状态始终处于正常范围,舒适性程度随视距增大而减小.     

土壤中石油污染物的脱附过程

文章中主要采用有机溶剂萃取法（OSE）对高浓度石油污染土壤进行修复，经过精馏操作，有效回收原油，建立脱附等温曲线，研究了石油污染物在土壤-有机溶剂两相间的迁移规律。