运动导致模糊的舌像的清晰化

在舌像采集过程中,根据运动造成舌像迷糊的特点分析由于匀速直线运动造成舌像模糊的原因,同时提出消除由于相对运动产生模糊的方法,并提出消除模糊的模型.实验表明,这一方法适用于舌像运动模糊的消除性,处理后的舌像有利于后续的图像处理.     

基于提升小波的运动模糊图像恢复

高频噪声对运动模糊图像的经典频域恢复方法影响较大,针对上述问题采用原方法存在运算量大的缺陷,提出了一种基于提升小波的运动模糊图像恢复方法:即对含噪运动模糊图像用9/7提升小波进行变换;对变换所得的低频包含运动模糊的部分用经典频域方法进行恢复,对变换所得的高频部分采用软域值自适应去噪处理;最后,对两部分处理结果进行9/7提升小波逆变换。仿真实验结果表明,方法能够较好的对运动模糊图像进行恢复。     

单图像盲去模糊方法概述

图像去模糊长期以来一直是计算机视觉和图像处理中的研究热点.由相机抖动、物体运动或失焦引起的运动模糊或焦点模糊图像会严重影响图像的使用和后续处理.传统的盲去模糊方法利用图像运动模糊产生的不同原因,可将运动模糊分为全局运动模糊和局部运动模糊.概述了近年来图像盲去模糊的方法和研究现状.在深度学习图像去模糊方法的基础上,总结了...     

一种新的运动模糊图像恢复方法

通过对运动模糊产生原因的分析,提出了一种去运动模糊的新方法。首先应用Hough变换和自相关函数估计出运动模糊的方向和长度,然后应用迭代步长自适应的整体变分模型进行图像恢复。实验结果表明,这样的空间域处理方法,不但可以避免传统的频率域去模糊方法产生的震铃效应,而且该方法具有良好的抗噪性和对运动模糊参数估计误差的低敏感性。     

基于双L_0稀疏先验的图像运动去模糊

目前图像的运动去模糊方法在处理较复杂的运动模糊时难以得到理想的效果,其原因之一是这些方法普遍只考虑图像梯度的稀疏性,忽略了模糊核的稀疏性。针对这一不足提出一种新的双L_0正则约束的运动模糊去除方法,该方法同时对自然图像梯度和模糊核使用L_0正则约束,结合半正定二次分裂最小化的方法进行求解优化,实现自然模糊图像梯度和模糊核均稀疏下的模糊核估计,并进一步使用L_(0.5)超拉普拉斯正则约束项恢复最终图像。实验发现,该方法可以较好地去除单幅图像较复杂的运动模糊,更好地克服了估计的模糊核中存在的噪点和错误,得到较现有方法更加理想去模糊效果。     

基于运动分割的视频去模糊

针对目前视频去模糊方法难以处理大幅度相对运动模糊,并且很难得到在时间和空间都保持一致性的去模糊结果的问题,提出基于运动分割的视频去模糊方法.基于视频序列清晰程度不同的前提下,用视频中的清晰块恢复模糊帧.根据模糊帧与其相邻的清晰帧的光流信息,将2帧之间存在的相对运动分割为独立的处理对象;不同运动对象分别估计模糊函数,并利用该模糊函数将清晰帧模糊处理;对模糊帧中的每一块区域,在被模糊处理后的帧中查找最相似的区域,利用对应清晰区域替换模糊区域;不同区域之间采用纹理融合,重建出清晰帧,实现对视频中大幅度相对运动去模糊.该方法基于并行思想设计和实现,利用GPU并行能力完成加速.实验结果证明,采用该方法不仅速度快,而且有效地解决了视频中大幅度相对运动模糊,并可以保持运动对象纹理结构的完整性.     

基于Gaussian-Hermite矩的旋转运动模糊不变量

目的 模糊图像的分析与识别是图像分析与识别领域的重要方向。有些图像形成过程中成像系统与物体之间存在相对旋转运动,如因导弹高速自旋转造成的制导图像的旋转运动模糊。大多数对于这类图像的识别都需要先对模糊图像进行“去模糊”的预处理,且该类方法存在计算时间复杂度较高及不适定的问题。对此,提出一种直接提取旋转运动模糊图像中的不变特征,用于旋转运动模糊图像目标检索和识别。方法 本文以旋转运动模糊的退化模型为出发点,提出了旋转运动模糊Gaussian-Hermite (GH)矩,构造了一组由5个对旋转变换和旋转运动模糊保持不变性的GH矩不变量组成的特征向量(rotational motion blur Gaussian-Hermite moment invariants,RMB_GHMI-5),可从旋转变换和旋转运动模糊的图像中直接进行目标检索和识别,无需前置复杂的“去模糊”预处理过程。结果 在USC-SIPI (University of Southern California — Signal and Image Processing Institute)数据集上进行不变性实验,对原图进行不同程度的旋转变换叠加旋转运动模糊处理,证明RMB_GHMI-5对于旋转变换和旋转运动模糊具有良好的稳定性和不变性。在两个数据集上与同类4种方法进行图像检索实验比较,在80%召回率下,本文方法维数更少,相比性能第2的特征向量,在Flavia数据集中,高斯噪声、椒盐噪声、泊松噪声和乘性噪声干扰下的准确率分别提高25.89%、39.95%、22.79%和35.80%;在Butterfly Image数据集中,高斯噪声、椒盐噪声、泊松噪声和乘性噪声干扰下的准确率分别提高4.79、7.63%、5.65%和18.31%。同时,在上述8个测试数据集中进行对比实验以验证融合算法的有效性,结果表明本文提出的GH矩和几何矩相融合算法显著改善了图像检索效果。结论 本文提出的RMB_GHMI-5特征向量在旋转变换和旋转运动模糊下具有良好的不变性与稳定性,在图像检索抗噪性能方面表现优异。相比同类方法,本文方法更具实际应用价值。     

一种改进的运动模糊图像恢复算法

在运动图像复原的研究中,运动模糊图像的参数估计与恢复算法是近年来数字图像处理领域研究的热点问题.针对运动图像受到噪声信号的影响,为了提高图像恢复效率,通过对运动模糊图像的恢复过程进行分析,提出了一种改进的参数估计与图像恢复算法,即利用经阈值化处理的Radon变换估计模糊方法,通过微分自相关法估计模糊长度,最后应用带最优窗的维纳滤波进行图像复原.进行仿真的结果表明,改进算法能够较为精确地估算出运动模糊图像的模糊参数并取得了较好的恢复效果,提升了图像恢复的抗噪性能,具有实际参考价值.     

图像复原中的模糊参数估计

图像复原技术在航空拍摄和机器视觉中是提高图像质量的重要手段.针对有相对运动情况的图像存在的降质模糊,分析了运动模糊的数学原理,针对不同运动模糊采取了不同去模糊方式.即先判断图像存在的运动模糊方式,针对直线运动通过Hough变换法和误差参数法相结合的方法估计降质参数,而对于旋转运动则采用曲线拟合和极坐标转换相结合的方法来估计降质参数.通过维纳滤波方法复原图像,提高图像质量.利用提出的自适应方法对直线运动模糊(参数为(30,70°))和旋转运动模糊(参数为(128,128),20°)分别作了实验计算.对比实验表明,这种由粗及精的方法能准确估计模糊参数,与传统处理方法相比,更加便捷有效.     

一种运动模糊图像的模糊参数估计方法

在摄取图像的过程中,物体间的高速运动及景物与成像设备的相对运动是引发图像退化的主要原因之一,称之为运动模糊。模糊长度和模糊方向是运动模糊中影响图像模糊程度的主要参数。提出了一种改进的误差参数分析方法,对模糊长度进行估计并比较了不同的复原方法对参数误差曲线法估计的效果,同时提出运用傅里叶分解和Hough变换从模糊图像的频谱特性上对运动模糊方向进行了估计。实验结果表明,所提出的方法对运动模糊图像的复原有良好的效果。     

Effect of global position information in unknown world exploration — A case study using the Teleworkbench

This paper presents empirical results of the effect of the global position information on the performance of the modified local navigation algorithm (MLNA) for unknown world exploration. The results show that global position information enables the algorithm to maintain 100% success rate irrespective of initial robot position, movement speed, and environment complexity. Most mobile robot systems accrue an odometry error while moving, and hence need to use external sensors to recalibrate their position on an ongoing basis. We deal with position calibration to compensate the odometry error using the global position information provided by the Teleworkbench, which is a teleoperated platform and test bed for managing experiments using mini-robots. In this paper we demonstrate how we incorporate the global position information during and after the experiments.     

A personal perspective on photowork: implicit human–computer interaction for photo collection management

In the age of digital photography, the amount of photos we have in our personal collections has increased substantially along with the effort needed to manage these new, larger collections. This issue has already been addressed in various ways: from organization by meta-data analysis to image recognition and social network analysis. We introduce a new, more personal perspective on photowork that aims at understanding the user and his/her subjective relationship to the photos. It does so by means of implicit human–computer interaction, that is, by observing the user’s interaction with the photos. In order to study this interaction, we designed an experiment to see how people behave when manipulating photos on a tablet and how this implicitly conveyed information can be used to aid photo collection management.     

Using physical memorabilia as opportunities to move into collocated digital photo-sharing

The uptake of digital photos vs. print photos has altered the practice of photo-sharing. Print photos are easy to share within the home, but much harder to share outside of it. The opposite is true of digital photos. People easily share digital photos outside the home, e.g., to family and friends by e-mail gift-giving, and to social networks and the broader public by web publishing. Yet within the home, collocated digital photo-sharing is harder, primarily because digital photos are typically stored on personal accounts in desktop computers located in home offices. This leads to several consequences. (1) The invisibility of digital photos implies few opportunities for serendipitous photo-sharing. (2) Access control and navigation issues inhibit family members from retrieving photo collections. (3) Photo viewing is compromised as digital photos are displayed on small screens in an uncomfortable viewing setting.To mitigate some of these difficulties, we explore how physical memorabilia collected by family members can create opportunities that encourage social and collocated digital photo-sharing. First, we studied (via contextual interviews with 20 households) how families currently practice photo-sharing and how they keep memorabilia. We identified classes of memorabilia that can serve as memory triggers to family events, trips, and times when people took photos. Second, we designed Souvenirs, a photo-viewing system that exploits memorabilia as a social instrument. Using Souvenirs, a family member can meaningfully associate physical memorabilia with particular photo-sets. Later, any family member can begin their story-telling with others through the physical memento, and then enrich the story by displaying its associated photos simply by moving the memento close to the home's large-format television screen. Third, we re-examined our design premises by evoking household reactions to an early version of Souvenirs. Based on these interviews, we redesigned Souvenirs to better reflect the preferences and real practices of photo and memorabilia use in the home.     

Visualizing Social Photos on a Hasse Diagram for Eliciting Relations and Indexing New Photos

Social photos, which are taken during family events or parties, represent individuals or groups of people. We show in this paper how a Hasse diagram is an efficient visualization strategy for eliciting different groups and navigating through them. However, we do not limit this strategy to these traditional uses. Instead we show how it can also be used for assisting in indexing new photos.Indexing consists of identifying the event and people in photos. It is an integral phase that takes place before searching and sharing. In our method we use existing indexed photos to index new photos. This is performed through a manual drag and drop procedure followed by a content fusion process that we call ’propagation’. At the core of this process is the necessity to organize and visualize the photos that will be used for indexing in a manner that is easily recognizable and accessible by the user. In this respect we make use of an Object Galois Sub-Hierarchy and display it using a Hasse diagram. The need for an incremental display that maintains the user’s mental map also leads us to propose a novel way of building the Hasse diagram. To validate the approach, we present some tests conducted with a sample of users that confirm the interest of this organization, visualization and indexation approach. Finally, we conclude by considering scalability, the possibility to extract social networks and automatically create personalised albums.     

图像适应算法中非冗余显著图的计算

近些年为了将大尺寸数字图像的内容自适应地显示在手机、PDA（掌上电脑）等屏幕较小的显示终端上以得到更好的显示效果,图像适应得到了很大的关注。现有的大量方法使用了不同的重要度映射来得到最优的图像缩放结果。图像适应算法就是为了去除图像中的不重要信息,为此提出在图像适应方法中使用非冗余显著图的计算来分析不重要信息的位置。首先,引入了图像分解,提出图像高梯度区域的冗余信息。然后,提出纹理梯度的概念,并进一步针对细节信息建立了纹理冗余度分析机制。纹理梯度非常适合卡通图像分析,从而将现有图像适应方法推广到非真实图像。大量实验结果显示,本文方法并不受图像适应算子的影响,该方法对具有复杂背景和包含多目标物体等的图像适应问题都比较鲁棒。     

EXCEL宏制作证件照

EXCEL电子表格在数据处理方面的功能是非常强大的,给我们的工作带来了方便,但在处理图片方面就显得有些欠缺了,如制作证件照,用常规的方法是无法完成的,而我们运用EXCEL的VBA功能可以轻松地制作证件照,实现特殊软件才能实现的功能。     

Delayed information cascades in Flickr: Measurement,analysis, and modeling

Online social networks exhibit small-world network characteristics, implying that information can spread in the network quickly and widely. This ability to spread information rapidly has led to high expectations for word-of-mouth and viral campaigns in online social networks. However, a recent study of the Flickr social network has shown that popular photos do not spread as quickly as one might expect, but show a steady linear growth of popularity over several years. In this paper, we investigate possible reasons for this delay in word-of-mouth propagation by studying the behavior of Flickr users. We identify two factors of a social network that can alter how information spreads: the burstiness of user login times and content aging. We study the impact of these factors using an epidemiological model that was adapted to allow us to investigate the speed of propagation in word-of-mouth propagation. Our simulation shows that the two factors can explain the patterns observed on the real data and help us to understand how these factors affect a small-world network’s ability to spread information quickly and widely.     

A hierarchical photo visualization system emphasizing temporal and color-based coherences

Most photograph management systems use a scrollable view based on a sequential grid layout that arranges photo thumbnails in some default order on the screen. Although users are very accustomed to this kind of photo layout, multiple drag and drop mouse interactions are required to search and obtain an overview of their photos. This paper describes a photo visualization system that visualizes hundreds of photos on a 2D grid space in order to help users manage their photos. Our system provides the following three main functions. First, it places similar photos in terms of color histogram and shoot time close together on the grid. Therefore, users can find their photos using temporal and color-based coherences relating to human sensory information such as colors that invokes similar feelings and photo shoot time. Second, our system provides a hierarchical clustering method based on a 2D grid space. This function can decrease drag and drop mouse interactions when classifying photos into small groups compared to the sequential grid layout. Finally, our system displays a representative photo from each cluster, in order to provide a summarized view of multiple photos. For evaluation of our system, we conducted seven experiments consisting of four computational and three subjective evaluations making a comparison with a sequential grid layout. The computational evaluations consider the four features of space efficiency, temporal stability and color-based consistency between neighbor photos of the grid, and cluster similarity. The evaluations establish that our system can decrease space efficiency while improving the other features. The three subjective evaluations deal with our system??s ease-of-use from a subjective human perspective. Most people that participated in our experiments found that this photo visualization system was quite suited to finding and summarizing their photo content.     

A model to estimate and interpret the energy-efficiency of movement patterns in urban road traffic

Urban road traffic is highly dynamic. Traffic conditions vary in time and with location and so do the movement patterns of individual road users. In this article, a movement pattern is the behaviour of a car when traversing a road link in an urban road network. A movement pattern can be recorded with a global navigation satellite system (GNSS), such as the Global Positioning System (GPS). A movement pattern has a specific energy-efficiency, which is a measure of how fuel-intensively the car is moving. For example, a car driving uniformly at medium speed consumes little fuel and, therefore, is energy-efficient, whereas stop-and-go driving consumes much fuel and is energy-inefficient. In this article we introduce a model to estimate the energy-efficiency of movement patterns in urban road traffic from GNSS data. First, we derived statistical features about the car's movement along the road. Then, we compared these to fuel consumption data from the car's controller area network (CAN) bus, normalized to the car's overall range of fuel consumption. We identified the optimal feature set for prediction. With the optimal feature set we trained, tested and verified a model to estimate energy-efficiency, with the fuel consumption serving as ground truth. Existing fuel consumption models usually view movement as a snapshot. Thus, the behaviour of the car remains unknown that causes a movement pattern to be energy-efficient or energy-inefficient. Our model views movement as a process and allows to interpret this process. A movement pattern can, for example, be energy-inefficient because the car is driving in stop-and-go traffic, because it is travelling at high speed, or because it is accelerating. Our model allows to distinguish between these different types of behaviours. Thus, it can provide new insights into the dynamics of urban road traffic and its energy-efficiency.     

The Beauty of Ugliness: Preserving while Communicating Online with Shared Graphic Photos

In this paper, we report on interviews with 11 Shia content creators who create and share graphic, bloody photos of Tatbeer, a religious ritual involving self-harm practices on Ashura, the death anniversary of the prophet Muhammad’s grandson. We show how graphic images serve as an object of communication in religious practices with the local community, the inner-self, and a wider audience. In particular, we highlight how content creators appropriated, in their own words, “ugly” photos to preserve the authenticity and beauty of their rituals while communicating their own interpretation of such rituals to others. We suggest that ugliness may be regarded as a useful resource to inform systems that seek to invite dialogue with marginalized or minority groups.