Locality preserving fusion of multi-source images for sea-ice classification

We present a novel sea-ice classification framework based on locality preserving fusion of multi-source images information.The locality preserving fusion arises from two-fold,i.e.,the local characterization in both spatial and feature domains.We commence by simultaneously learning a projection matrix,which preserves spatial localities,and a similarity matrix,which encodes feature similarities.We map the pixels of multi-source images by the projection matrix to a set fusion vectors that preserve spatial localities of the image.On the other hand,by applying the Laplacian eigen-decomposition to the similarity matrix,we obtain another set of fusion vectors that preserve the feature local similarities.We concatenate the fusion vectors for both spatial and feature locality preservation and obtain the fusion image.Finally,we classify the fusion image pixels by a novel sliding ensemble strategy,which enhances the locality preservation in classification.Our locality preserving fusion framework is effective in classifying multi-source sea-ice images(e.g.,multi-spectral and synthetic aperture radar(SAR)images)because it not only comprehensively captures the spatial neighboring relationships but also intrinsically characterizes the feature associations between different types of sea-ices.Experimental evaluations validate the effectiveness of our framework.

Multi-Scale PIIFD for Registration of Multi-Source Remote Sensing Images

This paper aims at providing multi-source remote sensing images registered in geometric space for image fusion.Focusing on the characteristics and differences of multi-source remote sensing images,a feature-based registration algorithm is implemented.The key technologies include image scale-space for implementing multi-scale properties,Harris corner detection for keypoints extraction,and partial intensity invariant feature descriptor(PIIFD)for keypoints description.Eventually,a multi-scale Harris-PIIFD image registration algorithm framework is proposed.The experimental results of fifteen sets of representative real data show that the algorithm has excellent,stable performance in multi-source remote sensing image registration,and can achieve accurate spatial alignment,which has strong practical application value and certain generalization ability.

Accuracy Analysis on the Automatic Registration of Multi-Source Remote Sensing Images Based on the Software of ERDAS Imagine

The automatic registration of multi-source remote sensing images (RSI) is a research hotspot of remote sensing image preprocessing currently. A special automatic image registration module named the Image Autosync has been embedded into the ERDAS IMAGINE software of version 9.0 and above. The registration accuracies of the module verified for the remote sensing images obtained from different platforms or their different spatial resolution. Four tested registration experiments are discussed in this article to analyze the accuracy differences based on the remote sensing data which have different spatial resolution. The impact factors inducing the differences of registration accuracy are also analyzed.

Image Processing on Geological Data in Vector Format and Multi-Source Spatial Data Fusion

The geological data are constructed in vector format in geographical information system (GIS) while other data such as remote sensing images, geographical data and geochemical data are saved in raster ones. This paper converts the vector data into 8 bit images according to their importance to mineralization each by programming. We can communicate the geological meaning with the raster images by this method. The paper also fuses geographical data and geochemical data with the programmed strata data. The result shows that image fusion can express different intensities effectively and visualize the structure characters in 2 dimensions. Furthermore, it also can produce optimized information from multi-source data and express them more directly.

An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D images.The current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time performance.To address these issues,we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space model.Then,an indoor RGB-D image semantic segmentation network is proposed,which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud model.Finally,Bayesian updating is used to conduct incremental semantic label fusion on the established spatial point cloud model.We also employ dense conditional random fields(CRF)to optimize the 3D semantic map model,resulting in a high-precision spatial semantic map of indoor scenes.Experimental results show that the proposed semantic mapping system can process image sequences collected by RGB-D sensors in real-time and output accurate semantic segmentation results of indoor scene images and the current local spatial semantic map.Finally,it constructs a globally consistent high-precision indoor scenes 3D semantic map.

基于Online AdaBoost的偏振图像目标跟踪

根据偏振图像的特点,文章提出一种基于在线AdaBoost的目标跟踪方法。该方法以最小二乘回归作为弱分类器,以强度、偏振度和边缘方向特征组成的向量为其输入;通过AdaBoost算法将多个弱分类器集成为强分类器,并在跟踪过程中利用AdaBoost算法对强分类器进行在线更新,以适应目标与背景的变化;利用强分类器生成当前置信图,在置信图上利用粒子滤波估计目标的状态。实验结果表明,该方法能够在复杂背景下稳定地跟踪目标。

A RBF classification method of remote sensing image based on genetic algorithm

The remote sensing image classification has stimulated considerable interest as an effective method for better retrieving information from the rapidly increasing large volume, complex and distributed satellite remote imaging data of large scale and cross-time, due to the increase of remote image quantities and image resolutions. In the paper, the genetic algorithms were employed to solve the weighting of the radial basis faction networks in order to improve the precision of remote sensing image classification. The remote sensing image classification was also introduced for the GIS spatial analysis and the spatial online analytical processing (OLAP), and the resulted effectiveness was demonstrated in the analysis of land utilization variation of Daqing city.

Smart Photogrammetric and Remote Sensing Image Processing for Very High Resolution Optical Images——Examples from the CRC-AGIP Lab at UNB

This paper introduces some of the image processing techniques developed in the Canada Research Chair in Advanced Geomatics Image Processing Laboratory (CRC-AGIP Lab) and in the Department of Geodesy and Geomatics Engineering (GGE) at the University of New Brunswick (UNB), Canada. The techniques were developed by innovatively/“smartly” utilizing the characteristics of the available very high resolution optical remote sensing images to solve important problems or create new applications in photogrammetry and remote sensing. The techniques to be introduced are: automated image fusion (UNB-PanSharp), satellite image online mapping, street view technology, moving vehicle detection using single set satellite imagery, supervised image segmentation, image matching in smooth areas, and change detection using images from different viewing angles. Because of their broad application potential, some of the techniques have made a global impact, and some have demonstrated the potential for a global impact.

Fast Image Segmentation Algorithm Based on Salient Features Model and Spatial-frequency Domain Adaptive Kernel

A fast image segmentation algorithm based on salient features model and spatial-frequency domain adaptive kernel is proposed to solve the accurate discriminate objects problem of online visual detection in such scenes of variable sample morphological characteristics,low contrast and complex background texture.Firstly,by analyzing the spectral component distribution and spatial contour feature of the image,a salient feature model is established in spatial-frequency domain.Then,the salient object detection method based on Gaussian band-pass filter and the design criterion of adaptive convolution kernel are proposed to extract the salient contour feature of the target in spatial and frequency domain.Finally,the selection and growth rules of seed points are improved by integrating the gray level and contour features of the target,and the target is segmented by seeded region growing.Experiments have been performed on Berkeley Segmentation Data Set,as well as sample images of online detection,to verify the effectiveness of the algorithm.The experimental results show that the Jaccard Similarity Coefficient of the segmentation is more than 90%,which indicates that the proposed algorithm can availably extract the target feature information,suppress the background texture and resist noise interference.Besides,the Hausdorff Distance of the segmentation is less than 10,which infers that the proposed algorithm obtains a high evaluation on the target contour preservation.The experimental results also show that the proposed algorithm significantly improves the operation efficiency while obtaining comparable segmentation performance over other algorithms.

Selling Luxury Brands in Online Private Sales Multibrand Retailers--An Exploratory Study of Consumers’Perspective

With Internet changing the luxury business landscape,new players have emerged such as the Online Private Sales Retailers(OPSRs).These offer online buyers with a choice of limited-time sales to help companies get rid of their overstocks.Luxury brands are no exception.No research has been conducted about how luxury consumers relate with such websites,hence this paper.In an exploratory fashion,interviews with luxury buyers who also buy online on OPSRs,are conducted to get insights on consumers’perceptions and luxury brand equity that selling through OPSRs may have.We find that appropriate product and brand help consumers forget that they are buying brands’unsold stocks,that transferring the luxury webmospheres would be positively perceived,that consumers from these websites are looking for benefits such as freedom of use and brand discovery,rather than personalized offers,that multiple discounts on several OPSRs may damage the luxury-perception of a brand,that the private sales members consider the service to be good enough for the demanded price,and that personalized invitations can help increase online consumers’feelings of desirability and exclusivity.The paper concludes with practical recommendations for both luxury companies and OPSRs.

医学影像学教学阅片实践课线上教学的优化探索

时代背景下,高校开展线上教学至关重要,在线教学模式多样,教学效果参差不齐。开展在线教育给教师带来了全新的机遇与挑战,为日后实施教育创造了有利的条件,在一定程度上促进了教育事业可持续发展。文章主要通过对医学影像学教学阅片实践课线上教学优化进行深度探究,首先,分析医学影像学线上教学的时代发展性、医学影像学教学阅片线上教学现状分析,其次从以案例为基础的教学法(case-based learning,CBL)、引入翻转课堂设计以及形成性评价方式等几个方面深入说明并探讨,为医学影像学在线教学阅片提供一种更生动有趣的教学模式,优化线上教学效果,以供其他学科参考。

联合多视角Transformer编码与在线融合互学习的乳腺癌病理图像分类模型

乳腺癌是女性最常见的癌症.单一网络在乳腺癌病理图像分类中存在缺陷,卷积神经网络无法提取全局上下文,而Transformer不能准确描述局部细节.本文提出联合多视角Transformer编码与在线融合互学习的乳腺癌病理图像分类模型(Multi-View Transformer Online Fusion Mutual Learning,MVT-OFML).采用ResNet-50(Residual Network-50)提取图像局部特征,设计多视角Transformer编码模块,捕获图像中全局上下文;联合Logits和中间特征层构建OFML框架,实现ResNet-50与多视角Transformer编码模块间双向传递知识,使2个网络优势互补以完成乳腺癌病理图像分类.实验表明,在BreakHis和BACH数据集上,MVT-OFML的准确率比最强基线分别提升0.90%和2.26%,F1均值比最强基线分别提升4.75%和3.21%.

蚕蛹性腺图像在线采集与雌雄自动识别分选装置设计与优化

针对当前蚕蛹雌雄鉴别环节人工劳动强度大、蚕蛹雌雄识别分选装置准确率和效率不高、适用品种范围小等问题,根据雌雄蚕蛹性腺特征差异是区别不同品种蚕蛹雌雄的可靠依据,该研究设计了一种蚕蛹性腺图像在线采集与雌雄自动识别分选装置。首先,在对蚕蛹基本物理特性参数大量统计的基础上,对振动排序上料机、蚕蛹输送滑轨和蚕蛹翻转拍照装置进行了结构设计与理论分析。在识别方法和计算机硬件条件不变基础上,对装置中蚕蛹排序输送螺旋倾角、滑轨倾角和转动棒带动蚕蛹旋转转速进行了优化设计,以提高装置的识别分选速度。并设计了以SIEMENS-S7-200SMART-ST30为控制器,基于激光、光电传感器检测的信息融合控制系统。分选装置工作性能优化结果为:螺旋倾角为15.62°,滑轨倾角为31.77°,转速为21.09 r/min,单粒蚕蛹平均分选时间为5.13 s,准确率为95.97%,破损率为0.07%。样机试验结果表明,在最优参数下,利用卷积神经网络的全新轻量级雌雄识别分类模型,单粒蚕蛹平均分选时间为5.03 s,分选准确率为96.47%,破损率为0.09%,满足蚕蛹雌雄识别分选实际应用要求。该蚕蛹性腺图像在线采集与雌雄自动识别分选装置能够实现蚕蛹自动排序上料、蚕蛹带性腺图像在线采集、自动识别与雌雄自动分选的一体化,提高了蚕蛹雌雄自动识别分选的效率和准确率。研究结果可为雌雄蚕蛹自动识别分选装置的研发提供理论依据和技术支持。

医学生对医学影像线上教学认可度的调查研究

目的了解医学专业学生对于线上教学的态度和看法。方法于2022年8—9月通过问卷星网络应用程序设计医学影像线上教学相关调查问卷,并在全国范围内通过互联网收集2019年1月—2022年7月参加线上学习的学生关于此次调查的回答。结果共有141名学生参与了此次调查,其中医学影像专业学生78名,非医学影像专业学生63名。90.78%(128名)的学生熟悉线上学习,且73.05%(103名)的学生受过线上学习的培训,57.45%(81名)的学生更倾向于线上与线下相结合的教学方式。对于医学影像线上学习的授课方式,10.64%(15名)的学生非常满意,43.97%(62名)的学生满意,仅有个别学生不满意或非常不满意。49.65%(70名)的学生认为线上教学尽可能地保持了教学质量,仅4.96%(7名)的学生认为没有保持教学质量。59.58%(84名)的学生认为医学影像线上教学与其他学科没有区别,31.91%(45名)的学生认为医学影像较其他学科更适合线上学习,只有8.51%(12名)的学生认为医学影像更适合于线下学习。结论线上教学是一种新型的教育方式,全面有序地开展线上教学活动可实现医学影像教学的全流管控,获得良好的教学效果。此外,为了进一步提高医学影像教学质量,线上与线下相结合的教学模式不失为一种较好的选择,是今后医学影像教学的主要方向。

城市图书馆新馆空间感知与评价——以“文旅打卡”为视角的混合研究

中国城市图书馆发展重心正经历着从资源服务到空间场景营建的变化。社会公众对作为文旅打卡地的新馆空间感知评价及其形象生成,拓展了以用户为中心的图书馆绩效与成效集合评价体系。以上海图书馆东馆为例,混合运用词频分析法识别新馆空间实体形象和附生形象,挖掘新馆空间形象体现维度,采用情感分析法分析用户情感倾向以及用户视角的新馆空间建设成效,并使用扎根理论挖掘用户旅游在线评论文本,构建用户视角的城市图书馆新馆空间形象感知模型。研究发现,城市图书馆作为重要的文化和旅游目的地,新馆用户认同水平仍有提升空间,其社会形象仍待建构完善且新馆用户感知仍需不断强化,需要增进新馆建筑的整体设计、凸显新馆场所的价值导向、激发新馆空间的体验氛围和提升新馆场景的文化内涵。

良渚在海外网络媒体中的形象研究

良渚文化作为一种被“重新发现”的地区文化,在中华文明发展进程中占据极其重要的地位。研究借助NOW新闻语料库,采用语料库和话语分析相结合的方法,从词频统计、搭配词分析、索引行分析等层面,对海外网络媒体关于良渚报道话语中的结构、意义和社会属性进行量化分析,并结合话语分析理论进行文本描述,定量与定性结合,观察良渚在海外网络媒体中的话语表征和形象描述,提出提升良渚国际形象的建议。

信息化时代“图像处理技术”课程建设与实践

文章针对信息化背景下学习活动模块化、时间碎片化和普通高等教育电子信息类专业课教学的自身特性,利用一体化平台整合教学资源,开展线上线下双线教学,同时实现教学全过程动态管理和成绩评价指标的量化记录;根据“图像处理技术”课程实践性强、应用广泛的特点,结合科研工程案例,利用平台开展翻转课堂形式的教学活动,并在教学过程中融入思政元素,激发学生学习积极性,增强学生的法律意识和科技强国的责任感;同时完善课程考核体系,提高课程参与度,取得了一定的实践效果。

研究生在线课程建设及混合式教学改革——以数字图像处理与分析课程为例

数字图像处理与分析是人工智能学科研究生教育的一门重要专业课。针对数字图像处理与分析研究生课程教学中,授课时间不足、教学资源相对缺乏、理论教学与实验环节脱节和课程思政内容较少等问题,构建在线精品课平台,对传统教学模式进行改革,推进线上线下混合式教学模式。注重课程体系构建与教学内容创新,整合视频、课件、案例库等资源,建设线上教学平台,充实课程思政及实践实验工程训练内容,结合课前、课上、课后三个教学阶段的特点,开展混合式教学。以武汉理工大学为例,验证教学模式的改革效果。

新工科背景下数字图像与视频处理课程混合式教学的探索与实践

新工科发展背景下数字图像与视频处理课程传统单一的教学模式和教学方法已无法有效地适应新时代高素质人才培养要求,新工科要求课程的教学内容、教学模式和考核方式等要素不断更新。为改进陈旧的教学模式、激发学生的学习主动性、提升学生的创新思维及编程实践能力,提出通过开展线上线下混合式教学、线下课堂实施六步教学法、课程资源建设、融合课程思政、构建验证性基础实验+综合实验+创新性项目实践的阶梯型实践教学体系、改进教学评价方式等多种改进措施,深化课程教学改革,提高了课程教学质量,取得了良好的教学效果。

文旅融合视域下基于在线评论的“网红”城市书房形象感知研究

文章借助Python软件、“微词云”工具及旅游地形象“认知-情感-整体”三维模型分析游客对4家“网红”城市书房的形象感知情况。研究发现,认知形象感知方面,游客对4家城市书房的认知印象各异;情感形象感知方面,大部分游客对各城市书房给予了积极评价,少部分游客作出了失望、遗憾等消极评价;整体形象感知方面,4所城市书房给游客留下了较为满意的印象,游客的重游或推荐热情较高。据此提出科学规划布局、改进内部设施、优化空间环境、增强多元功能、落实管理责任等文旅融合视域下城市书房发展建议。