图像分割

此算法实现了分形图形分形树的一种叠代算法的实现过程。它充分利用了叠代的思想(algorithm achieved a fractal graphics fractal tree an iterative algorithm implementation process. It makes full use of iterative thinking)

说明：  实现了图像与视频的信息隐藏，输入图片和视频可进行效果演示(The information hiding of image and video is realized)

demons 配准非常好用的非刚体配准！(Registration is very easy demons non-rigid registration!)

说明：  根据一幅杂草和作物混合的图像可以识别出图像中的杂草(Weeds in the image can be identified according to a mixed image of weeds and crops)

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. )

说明：  快速磁共振成像领域的GRAPPA（generalized auto-calibrating partially parallel acquisitions）算法实现(GRAPPA realization in fast MRI)

说明：  用于图像去噪处理，使用ADM方法图像去噪处理器处理(Used for image denoising processing, using adm method image denoising processor processing)

sar 图像边缘检测算子，代码简洁，能够运行成功。(sar image edge detection，it s simple and useful 。)

非降采样Contourlet域内空间频率激励的PCNN图像融合算法的实现代码(Non-spatial frequency domain down-sampling Contourlet motivated PCNN image fusion algorithm implementation code)

基于颜色特征向量的粒子滤波跟踪程序，修复了因粒子超过窗口范围出现ERROR的BUG，还包括了一些有助于粒子滤波学习的资料！！(color-based particle filter tracking, some bugs have been fixed, some information about PF Tracking is included too!!)