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matlab的gui设计程序,有关<信号与系统>课程的辅助教学设计(Matlab GUI design, the relevant & lt;)

比较新的图像处理类，2010版，并且有DEMO,方便应该(Relatively new class of image processing, 2010 Edition, and has DEMO, should facilitate)

说明：  图像处理所涉及的256转灰度，二值化等等，每个部分都是独立可执行的工程文件，很方面的代码复用(256 involved in image processing turn gray, binary, etc., are independent of each part of the project executable file, it' s code reuse)

图像DFT，C语言编写的代码，附带几个另外的处理，(Image DFT, C language code, with some additional processing,)

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. )

包括基于SIFTGPU的sift特征提取，sift匹配，基于ransac误匹配点剔除等(SIFTGPU based sift feature extraction, sift matching, mismatching points based ransac removed, etc.)

通过数字图像相关的方法计算两幅图像之间的位移，计算时间较长，是最基础的DIC，没有优化。(Digital image correlation method to calculate the displacement between the two images, the time is longer, is the most basic DIC, no optimization.)

傅里叶时域频域变换图形处理S参数在时域的应用(Fourier time domain frequency domain transform graphics processing S-parameters in the application of the time-domain)

图像质量评价，计算两幅图像的保真性，鲁棒性 ，结构相似性 (Image quality assessment，calculate the fidelity ，robust and structural similarity of the image，)

Shap Context based Shape recognition