Adaptive variational models for image decomposition

Image decomposition refers to the splitting of an image into two or more components.In this paper,a clean image is separated into two parts:one is the cartoon component,consisting only of geometric structure,and the other is the oscillatory component,consisting of texture.Three parts for noisy image are considered:cartoon,texture,and noise.To better decompose an image,we propose two new variational models.In our models,two adaptive regularization terms are introduced.The two regularization terms are determined by an adaptive function which can discriminate the cartoon and texture of an image automatically.Experimental results illustrate the efectiveness of the proposed models for image decomposition.     

Temporal evolution of contacts and communities in networks of face-to-face human interactions

Temporal dynamics of social interaction networks as well as the analysis of communities are key aspects to gain a better understanding of the involved processes, important influence factors, their effects, and their structural implications. In this article, we analyze temporal dynamics of contacts and the evolution of communities in networks of face-to-face proximity. As our application context, we consider four scientific coil- ferences. On a structural level, we focus on static and dynamic properties of the contact graphs. Also, we analyze the resulting community structure using state-of-the-art automatic community detection algorithms. Specifically, we analyze tile evolution of contacts and communities over time to consider the stability of the respective conmmnities. Furthermore, we assess different factors which have an influence on the quality of com- munity prediction. Overall, we provide first important insights into the evolution of contacts and communities in face-to-face contact networks.     

Fractional partial differential equation denoising models for texture image

In this paper,a set of fractional partial differential equations based on fractional total variation and fractional steepest descent approach are proposed to address the problem of traditional drawbacks of PM and ROF multi-scale denoising for texture image.By extending Green,Gauss,Stokes and Euler-Lagrange formulas to fractional field,we can find that the integer formulas are just their special case of fractional ones.In order to improve the denoising capability,we proposed 4 fractional partial differential equation based multiscale denoising models,and then discussed their stabilities and convergence rate.Theoretic deduction and experimental evaluation demonstrate the stability and astringency of fractional steepest descent approach,and fractional nonlinearly multi-scale denoising capability and best value of parameters are discussed also.The experiments results prove that the ability for preserving high-frequency edge and complex texture information of the proposed denoising models are obviously superior to traditional integral based algorithms,especially for texture detail rich images.     

基于倒位变异的蜉蝣优化算法

蜉蝣算法(Mayfly Algorithm,MA)作为一种新型群智能优化算法,具有较好的寻优性能.但在高维非线性复杂问题上,蜉蝣算法依然容易出现早熟收敛现象.本文提出一种基于倒位变异的蜉蝣算法(Inversion Variation Mayfly Algorithm,IVMA),改变原算法在变异上的操作,随机选择个体的随机维度向全局最优个体的随机维度靠近,同时利用精英策略保留进化成果.利用倒位操作,将最优个体某一维度段内位置发生倒转,提高了算法跳出局部最优的能力.通过对10个测试函数的结果分析,表明本文所提出的算法具有较好的收敛精度,收敛性能得到了提高.     

多特征融合和尺度变化估计的船舶跟踪方法

传统的船舶视觉跟踪任务主要集中于单目标船舶跟踪,对多目标船舶跟踪研究相对较少。为解决该问题,提出一种多维特征融合机制和尺度变化估计的多目标船舶跟踪框架,该框架引入位置滤波器对输入的船舶训练样本进行学习,并将其应用于待跟踪的船舶图片序列,通过寻找最大响应的方法判定图像中的船舶位置。在此基础上,构建船舶尺度估计滤波器以确定待跟踪船舶的图像尺寸。通过和中值流跟踪算法和多示例学习跟踪算法对比分析,实验结果表明不同海事交通场景下的船舶跟踪误差均小于10像素,验证了算法的有效性和可靠性。     

深圳市降水变化特征及其未来变化情况预测

基于1998—2018年深圳市日降水资料,采用降水相对变率、集中度及集中期分析了月尺度、年尺度降水稳定性及其年内分配特征,运用Mann-Kendall非参数法和相关函数法对深圳市年降水量、降水稳定性和分配特征参数的变化趋势、突变特征及其未来降水变化特征进行分析与预估。结果表明:深圳市汛期降水稳定性比非汛期更好,年际降水分布稳定性较差,降水集中期为每年6—8月份,降水集中度处于0.23~0.72;降水量和降水分布特征参数均在2011—2013年发生突变,在发生突变后降水相对变率和集中度呈下降趋势,而年降水量和集中期呈上升趋势;深圳市未来降水序列变化趋势受过去变化特征的影响,其中未来年降水量有减少的趋势,降水集中程度逐渐增强,降水稳定性逐渐变差,年内降水分配均匀性变差,降水集中期持续向后推迟。研究成果为深圳市合理蓄水和用水提供科学依据,对水资源调度、利用以及防汛抗旱具有实际指导意义和重要的学术价值。     

1951—2013年周口地区降水时空变化特征研究

为了研究区域降水的时空演变规律,根据周口地区28个雨量站1951—2013年的月降水量实测资料,利用经验正交函数(EOF)分析法、Mann-Kendall检验法及Morlet小波分析法,分析了周口地区63年来降水的空间分布、时间系数变化特征和时间序列的趋势性、突变性及周期性。结果表明,周口地区降水的空间分布有3种模式:全市丰(枯)一致型、南丰(枯)北枯(丰)型和东丰(枯)西枯(丰)型,其中全市丰(枯)一致型为周口地区降水的主要分布模式,其中1966年的全市降水偏枯和2003年的全市降水偏丰最为典型;周口地区降水量由东南向西北逐渐减小,各站点降水趋势变化不一,西南部呈下降趋势,中北部呈上升趋势,降水总体呈下降趋势;区域整体降水在1997年发生了突变,整体降水周期性变化明显,存在时间尺度为21 a的变化周期。研究结果可为周口地区的农业生产以及旱涝预警和减灾防灾提供理论支撑。     

结合自适应稀疏表示和全变分约束的图像重建

In view of the limitation of fixed complete orthogonal transformation, represented by two-dimensional wavelet transform and discrete cosine transform in compressed sensing high-resolution image reconstruction, this paper proposes a new method for high-resolution image reconstruction based on adaptive redundant dictionary sparse representation with the total variation constraint.The algorithm takes the intermediate image in the process of iteration as the training sample to get a redundant dictionary suitable for sample characteristics by adaptive learning. It makes full use of the correlation between dictionary atoms and the image to get an ideal complete sparse representation, thus reducing the sampling rate and improving the quality of image reconstruction. Finally, the algorithm takes the total variation as a constraint and uses the split Bregman iterative method to solve the sparse optimization problem. Simulation shows that the proposed method can reconstruct high quality images under a low sampling rate.     

基于Landsat遥感影像的黄河三角洲东营段海岸线变化分析

基于Landsat遥感影像数据,利用平均高潮线法提取了1986—2015年的海岸线,运用GIS技术分析了黄河三角洲东营段面积的淤蚀变化、海岸线迁移特征及其时空变化规律,以及淤蚀变化与入海水沙的关系。结果表明:1986—1997年黄河三角洲东营段处于持续蚀退状态,蚀退面积约为180 km~2;1997—2006年淤积后面积相对稳定,2006年面积和1986年相差不大;自2008年开始呈现轻微蚀退状态;蚀退速率和淤积速率最快的时段分别为2011—2013年和1997—1999年。海岸线时空变化特征显著,黄河入海口段变化最为剧烈,海岸线方向和形态不断变化,向海延伸;东营港及邻近岸段区域面积基本稳定;刁口段、莱州湾岸段年间淤进和蚀退交替进行,总体上均处于蚀退状态。黄河三角洲东营段海岸线变化主要受黄河流路变化、入海水沙和海水侵蚀的影响,黄河调水调沙工程的长期实施对于近年来河口海岸线的变迁具有深刻影响。     

基于雪岭云杉树轮的阿克苏河干流冬季径流重建

基于阿克苏河上游高山区采集的雪岭云杉树轮样芯构建了雪岭云杉树轮宽度年表,结合阿克苏河干流径流数据解析了雪岭云杉长期生长与阿克苏河干流径流关系,并重建了阿克苏河干流1813—2015年冬季径流序列。结果表明:利用雪岭云杉树轮宽度年表重建的阿克苏河干流1813—2015年冬季径流序列模拟值与实测值吻合度较高,重建径流序列稳定可靠;1813—2015年阿克苏河干流冬季多年平均流量为82.19 m~3/s,共出现5次持续丰水期和3次持续枯水期,最长的枯水段持续17年(1943—1959年);阿克苏河干流冬季径流变化存在51 a、29 a、16 a周期,第一主周期为51 a。