leijiayanse

说明：  可以对光谱数据进行预处理，除了偏最小二乘法之外，也有一些其他方法(Besides the partial least square method, there are also some other methods)

机器人视觉工具箱,有丰富的例程.进行视频监控,目标检测与跟踪有用.(Visual robot kit has a wealth of routine. To conduct video surveillance, target detection and tracking useful.)

生成SAR图像程序，可以生成幅度SAR图像和强度SAR图像。(This procedure generate SAR images, and it can generate the amplitude SAR image and the intensity SAR image .)

【实例简介】转自CSDN分享，使用时只需改opencv路径，可成功编译。

给予稀疏编码的原理将10幅自然图像进行系数分解成为图像基。(Given to the principle of sparse coding will be 10 coefficients of natural images into separate image-based.)

说明：  使用openmv实现人脸识别。。。。。。。。。。。。。。。。。。(Face recognition is a kind of biometric technology based on facial feature information. A series of related technologies, also known as portrait recognition and face recognition, that use cameras or cameras to collect images or video streams containing faces, and automatically detect and track faces in the images, and then perform face recognition on the detected faces.)

说明：  通过纹理方向估计消失点，通过消失点来检测道路区域。 该程序应用到了基于纹理的张量投票算法来估计消失点；通过纹理方向和颜色信息，生成用于估计两个最主要道路边界的直方图；最后将道路区域定义为两个检测到的道路边界之间且低于估计的消失点的区域(The vanishing point is estimated by the texture direction, and the road area is detected by the vanishing point. The program applies a texture-based tensor voting algorithm to estimate the vanishing point; through the texture direction and color information, generates a histogram for estimating the two most important road boundaries; finally defines the road area as two detected road boundaries. An area between and below the estimated vanishing point)

常见的几种去噪方法，维纳滤波器，均值滤波各种滤波(Extension of Phase Correlation to Subpixel Registration %Implementation of: % Extension of Phase Correlation to Subpixel Registration)

实现“动态”的位图动画，VC++经典编程学习源码，很好的参考资料。(The realization of "dynamic" bitmap animation, VC++ classic learning programming source code, a good reference.)

基于SUFT的特征提取与匹配，内涵详细的文档说明，很好的实现了特征提取与匹配，该方法较基本的SIFT有很大的提高(Extraction and matching of features based on SUFT, detailed content of the documentation, very good realization of the feature extraction and matching, SIFT the method is basic is greatly improved)