Generate-SAR-image

数字识别PCA方法，对其它图像同样适用，程序简便。(Digital identification PCA method, on the other images of the same application, the program is simple.)

前景检测 对动态背景进行多角度监测 动态背景检测(Foreground detection is used to monitor dynamic background from different angles)

online random forest 在线随机森林做跟踪和分类的代码(online random forest-line tracking and classification random forest to do the code)

提取图像的zernike特征参数，这个程序较难，关键这个是带程序说明的，让你一目了然(Extract images zernike characteristic parameters, this procedure is more difficult, the key to this is with a description of the procedures, at a glance)

图像融合技术，对可见光图像与红外图像进行融合。(Image fusion, image visible and infrared image fusion.)

softcast的2d dct实现，先对图像转灰度图，得到的亮度信号矩阵做DCT 变换(softcast of 2d dct implementation, the first image to grayscale, luminance signal obtained by DCT transformation matrix do)

相当的经典啊 是基于MATLAB的 大家做图像匹配的都可以用的到(Fairly classic MATLAB-ah is based on the U.S. to do image matching can be used to)

将原始载体图片经过一维冗余离散小波变换分成四个子频带，分别对每个子频带进行奇异值分解， 将水印图片灰度值直接按比例缩小嵌入到奇异值矩阵中，再将此矩阵进行一次奇异值分解得到奇异值当做此子带的奇异值， 重建此子带矩阵，而后将进行反冗余离散小波变换得到嵌入载体后的水印图像。(The original image after the one-dimensional vector redundant discrete wavelet transform is divided into four subbands, respectively, of each sub-band for the singular value decomposition, the watermark image gray value scale down directly embedded into the matrix singular value, then this matrix is ​ ​ a Singular value decomposition singular value as the singular values ​ ​ of this sub-band, the reconstruction of this sub-band matrix and after anti-redundant discrete wavelet transform watermark image after embedding the carrier.)

说明：  使用matlab平台进行斜视角为0度的九点目标RD算法仿真(Simulation of nine point target Rd algorithm with 0 degree squint angle using MATLAB platform)

归一化互相关算法是传统的图像匹配算法,针对传统图像匹配算法运算量大、速度慢的缺点,提出了一种基于小波变换的多尺度图像匹配算法。(Normalized cross-correlation algorithm is the traditional image matching algorithm, proposed a wavelet transform-based multi-scale image matching algorithm for the large amount of computation of traditional image matching algorithm, slow disadvantage.)