A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C₄ index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.     

Rats in a transparent morris water maze use elemental and configural geometry of landmarks as well as distance to the pool wall

The aim of this study is to evaluate whatare the dimensions of a panorama of discretelandmarks that a rodent will store in order toreturn to a previously visited target. Ratswere trained to locate a hidden platform in acircular pool of clouded water set within aquasi-spherical enclosure. In order to find theplatform, they had to learn the geometricrelations between the platform and asurrounding set of three discrete landmarks,highly visible through the transparent wall ofthe pool. In test trials without a platform,the array of landmarks was so manipulated as todissociate the effect of actual distance to thelandmarks, of their angular separation, and oftheir apparent dimension. Animals were shown torely equally on angular separation and apparentdimension. The role of actual distance couldnot be definitely ascertained, as animals wereshown to additionally rely on the distance tothe pool wall in order to locate theplatform.     

Function,geometry and spatial prepositions: Three experiments

In this paper the results of three experiments are reported whichaddress the issue of the relative extent to which functionalrelations versus geometric relations affect spatial language. Theexperiments examine the role of a discourse context on the useand rating of the preposition in to describe a visual scenewhere the constraint of spatial containment between figure(object located) and ground (reference object) does not hold. Allthree experiments demonstrate that in is used more andrated to be significantly more appropriate in a functionalcontext than in a no context condition. The implications of thesestudies for spatial language and spatial representation arediscussed.     

Representing a stable environment by egocentric updating and invariant representations

To represent a stable environment despite the experience of changes during self movements, one can either develop an invariant allocentric representation, or update the egocentric representations as one moves. Using a disorientation paradigm, three sets of studies investigated these mechanisms in human navigation and scene recognition. Accuracy in the configuration of multiple object localization is impaired by disorientation, an effect not due to artifacts such as memory deterioration over time, intervening physical activities, uncertainty in self position and orientation, etc., suggesting one can locate objects primarily by updating their egocentric positions as she or he moves. Disorientation also impaired the judgment of changes to a scene after viewer movements, suggesting a similar egocentric updating process. On the contrary, representation of the shape of the surroundings is invariant and persists through disorientation. The coexistence of multiple mechanisms may increase the flexibility and robustness of the system.     

一种基于高分辨率距离像自动目标识别新方法

提出了一种基于高分辨率距离像的联合对准与识别新方法。该方法结合功率变换的使用，在利用8米雷达目标实测数据进行的识别实验中，获得了较高的正确识别率。     

神经网络与D-S理论结合的HRR识别研究

基于D-S(Dempster-Shafer)证据理论,比较和研究了相关数据和不相关数据的融合方法,分析了多传感器数据融合的算法:集中式融合算法和分布式融合算法.经过实验证明,执行分布式有反馈融合算法时的效果最好.然后利用该算法,提出了和线性内插神经网络相结合的识别方法.利用4种飞机的步进频率雷达的高分辨率一维距离像,将神经网络的识别结果作为证据分别送入传感器进行融合,进行识别研究.实验证明,与单纯利用神经网络的方法比较,目标的正确识别率得到了改善.     

自适应DBF与空间谱估计

讨论了自适应数字波束形成(DBF)技术和超分辨空间谱估计技术,并提出了一种基于信号协方差矩阵特征分解的时-空二维信号高分辨谱估计算法。以上技术应用于相控阵雷达系统,可以精确获得多个运动目标的方位信息和多普勒信息。文章最后给出了计算机模拟结果。