CoSaMP-and-OMP-for-sparse-recovery_OK

找出sift关键点，形成特征向量，再进行描述(find the sift keywords,formed descreptors)

说明：  小波阈值去噪。对灰度图像和二值图像进行滤波。(Wavelet thresholding filter . Denoiseing for the gray image and binary image .)

利用双线性插值，获取亚像素位置的灰度值。适用于得到sift、surf得到的特征点坐标处的灰度值获取(The gray value of sub-pixel position is obtained by bilinear interpolation)

1．选择一幅图像，对该图像进行DCT块操作（将图像分成8×8小块，对每个小块进行DCT变换）。 2.利用屏蔽矩阵对DCT系数进行区域选择，然后进行逆变换（IDCT），合成原图像，计算合成图像的PSNR。 3.选择一小波函数，对一幅图像进行分解，显示各变换系数，观察其规律，并进行小波逆变换，合成原图像。 (1. Select an image, the image DCT block operations (the image is divided into 8 × 8 small pieces of each small piece for DCT transform). 2. The use of shielding on the DCT coefficient matrix of regional choices, and then inverse transform (IDCT), synthesis of the original image, calculating the synthetic image PSNR. 3. To select a wavelet function, decomposition of an image to show the transform coefficients, to observe its laws, and inverse wavelet transform, the original synthetic image.)

用PYQT进行GUI的详细资料，可以对照参考。。。。。。(The detailed information of GUI with PYQT can be compared to reference. The detailed information of GUI with PYQT can be compared to reference.)

实现瑞雷面波的频散曲线提取，并应用频散曲线模拟面波并成像，随即进行面波的逆频散(Inverse dispersion of the Rayleigh wave dispersion curve extraction and application of dispersion curves simulated surface wave imaging, then surface wave)

CV水平集模型实现对图像的分割，收敛快，收敛效果优于GAC 模型。(CV levelset model to realize image segementation)

附带GUI界面，可用于各种图像的特征点提取，并对两幅图像进行配准拼接，使用的是sift算法( U9644 u5E26G0 u754C u972 u53EF u7528 u4E8E u5404 u79V U8FDB u884C u914D u51C6 u62FC u63A5 uFF0C u4F7F u7528 u7684 u662Fsift u7B97 u6CD5)

程序将界面与数据处理分开，界面采用MFC的对话框模板，对注册、训练、识别和主界面分别建立一个类，通过消息处理函数与用户进行交互，利用多线程来实时显示图像。 数据处理又分为了CFaceAlign（人脸检测+几何归一化）、CLightPrep（光照归一化）、CFaceFeature（Gabor特征提取）、CSubspace（计算Fisherface子空间）四个类，还有一个类 CFaceMngr 负责管理界面与数据之间的交流。这样的程序结构使对界面和算法彼此独立，互不影响。 每个类的具体方法请见相应头文件中的注释。(The program will interface with the data processing separate interface using MFC dialog template, registration, training, recognition and the main interface, respectively, to create a class that interacts with the user through a message handler, using multiple threads to display images in real time.   Data processing is divided into a CFaceAlign (Face Detection+ geometric normalization), CLightPrep (illumination normalization), CFaceFeature (Gabor feature extraction), CSubspace (computing Fisherface subspace) four categories, as well as a class is responsible for managing CFaceMngr interface and data exchange between. Such a program structure allows for interfaces and algorithms are independent of each other. Specific methods of each class, see the comments in the appropriate header files.)

说明：  ISAR三维成像算法,可以用于matlab平台进行仿真(ISAR Three dimensional matlab)