DigitalPic_bighomework

此程序是基于灰度共生矩阵的图像纹理特征提取算法，它进行了四个方向上的灰度共生矩阵的计算，从而得出他们的纹理特征向量，再求均值，使计算进度大幅度提高(This program is based on the GLCM texture feature extraction algorithm, which was four directions GLCM calculation to arrive at their texture feature vector, and then seek means to significantly increase computing progress)

说明：  此程序是关于车牌识别重的一个重要环节——图像的二值化过程，希望能给你一些帮助(this program is heavy on the license plate to identify an important part of the-- the two values image process and hope to give you some help)

本代码建立高斯混合模型(高斯多模型)(GMM)，将其用于计算机视觉领域的视频目标检测/视频监控/运动检测/运动目标检测/视频目标跟踪等相关应用中。(This code sets up Gaussian mixture model(Gaussion Mixture Model, GMM) with image sequences for the research and application field of computer vision, using GMM for visual object detection(video object detection), visual surveillance, motion detection, motion tracking, visual object tracking, video object tracking, etc.)

对图形进行二维傅里叶变化后的频谱进行中心化(Centralization of the spectrum after two-dimensional Fourier transform)

本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法，以及4种算法之间的比较。四种反演算法为：TSVD、Chaine、Tikhonov和l1正则化。(The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a comparison between the four algorithms. Four kinds of inversion algorithm is: TSVD, Chaine, Tikhonov and l1 regularization.)

用matlab编写的SUSAN角点检测程序(Matlab prepared using SUSAN corner detection procedures)

说明：  利用蚁群算法对图片进行边缘检测，该方法速度较慢但是鲁棒性高(The ant colony algorithm is used to detect the edge of the image, which is slow but robust)

说明：  雷达发射波形。回波的模拟，以及匹配滤波。加窗控制旁瓣，以及MTD处理(Radar transmitting waveform. Echo simulation and matched filtering. Windowing control sidelobe and MTD processing)

图像处理（图像融合，图像加密等）的性能评价指标集包括：平均梯度，边缘强度，信息熵，灰度均值，标准差(均方差MSE)，均方根误差，峰值信噪比（psnr），空间频率(sf)，图像清晰度，互信息(mi)，结构相似性(ssim)，交叉熵(cross entropy)，相对标准差。(Image processing，average gradient, edge strength, information entropy, gray mean, standard deviation (variance (MSE), are root mean square error, peak signal to noise ratio (PSNR), spatial frequency (SF), the sharpness of the image, the mutual information (MI), similar to the structure of (SSIM) and cross entropy (cross entropy). The relative standard deviation)

Brown noise generated in Matlab