GSO-matlab

ICP是用来匹配两组未知点，可以用于图像处理等方面，速度快，但需要选择好初始参数(ICP is used to match two sets of unknown points can be used in areas such as image processing speed, but need to select a good initial parameters)

说明：  使用lbp算法来计算出一副图片的纹理程度，归一化处理(LBP calculates the texture level of the image)

SAR成像中的RD算法是最经典的校正算法之一，提供的代码有详细的注释和说明，欢迎大家下载学习(RD SAR imaging algorithm is one of the most classical calibration algorithm, the code provided detailed notes and descriptions, are welcome to download the study。)

基于多相结构的信道化接收机，sar图像去噪的几种新的方法，小波包分析提取振动信号中的特征频率。( Channelized receiver based on multi-phase structure, Several new methods sar image denoising, Wavelet packet analysis to extract vibration signal characteristic frequency.)

心电信号QRS复波实时检测代码及界面，使用QRS复波检测算法检测QRS复波(Code and interface, real-time detection of ECG QRS complex wave QRS complex wave detection algorithm to detect QRS complex wave)

人脸检测与跟踪，我的毕业论文，使用我自己改进的ADABOOST和CAMSHIFT算法,附带我的毕业论文,opencv1.0或以上自己配置(face detection use adaboost and camshift algorithm，relevant paper enclosed，OPENCV1.0 is necessary)

总变分正则化超分辨率重建 包括两种范数形式的正则化(Total Variation Regularized super-resolution reconstruction, including two-norm in the form of regularization)

用VC编写的一个图像处理的程序：它可以实现图像的增强，包括：图像的平滑、中值滤波、梯度锐化、拉普拉斯锐化和伪彩色编码(VC prepared by an image processing procedures : it can enhance the images, including : image smoothing, Median filtering, sharpening gradient, Laplacian sharpening and pseudo-color coding)

BM3D图像去噪算法。当下较为先进的图像去噪算法，可以对图像进行较好的去噪。在代码中包含了彩色图像，运动图像等多种bm3d去噪。(BM3D image denoising. Present a more advanced image denoising algorithm, can be a good image denoising. Included in the code of color images, moving images, and other bm3d denoising.)

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. )