SLIC超像素1

用matlab实现的欧拉影像放大应用程序。(Euler image magnification application realized by matlab.)

k均值聚类，类数可以自行指定，输出散点图，红色十字为聚类中心(K-means clustering, the class number can be specified on its own, the output scatterplot chart, and the Red Cross for clustering center)

说明：  能够对MRI数据进行功能成像，对于脑动态的检测具有重要意义(The ability to perform functional imaging on MRI data is of great significance for the detection of brain dynamics)

针对粒子概率假设密度(PH D)滤波算法在虚警、漏检情况下，b标状态估计不稳定和b标可观测性车弱的问题，提出了一种基于序贯融合的粒子PH D滤波方法，利用雷达和红外传感器多目标进行融合跟踪杏基本思想是先对红外传感器进行粒子PH D滤波，丙将红外传感器滤波结果作为雷达的预测值，然后利用P达观测的数据进行更新，这样通过雷达和红外传感器交替上作保证目标状态的可观测性，从滤波器输出结身即可得到目标的状态信息仿真结果表明，在虚警、漏检和密集目标环境下，该方法是有效的和稳健的(The problem of target state estimation instability and observability weakerin the presence offalse alarms and missed detection was deal with. On the basis of sequential fusion, a particleprobabil- ity hypothesis density(PHD) filter for multrsensor multrtarget tracking was proposed. Observed da to collected from the infrared sensor was estimated with the particle PHD filter. Then the results from the filter were set as the radar predicted value by the radar observations. The multrtarget state can be updated to guarantee observing the target state. In this way, the global state is updated at the fusion center. Simulation results show that the proposed algorithm is effective and robust under the false warning, omission and concentrated target environment. )

在图片上进行热点编辑，可进行区域的连接设置(Hotspot on the image editor, in the area can be connection Settings)

原始的criminisi灰度图像修复算法及实验图片(Original Criminisi grayscale image restoration algorithm and experimental images)

说明：  实现了监控视频图像的去隔行算法，使隔行扫描的图像插值成为逐行扫描(The realization of the surveillance video images Deinterlacing Algorithm, so deinterlacing Image Interpolation become progressive scan)

虹膜识别中的特征提取算法：2D-Gabor滤波器算法，将归一化的虹膜图像由此滤波器滤波，可以得到二进制的特征编码。附图片。(Iris recognition in the feature extraction algorithm: 2D-Gabor filter algorithm, the normalized iris image resulting filter can be obtained characteristics of the binary encoding. Attached picture.)

一种基于稀疏表示的图像融合方法，基于论文《Information Fusion》论文Joint patch clustering-based dictionary learning for multimodal image fusion 进行编写 结果相似(A sparse based image fusion method. It is based on paper Joint patch clustering-based dictionary learning for multimodal image fusion of Information Fusion The results is almost the same to this paper)

SVM支持向量机在图像分割中的应用，包含Matlab源代码和SVM所用函数。(SVM support vector machine applications, including image segmentation Matlab source code and functions used by SVM.)