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说明：  Forstner特征点提取算子，Matlab语言实现，亲测有效(Feature points detecting algorithm)

经典的数字图像处理的形态学处理，包含源代码(Digital image processing morphological processing)

合成孔径雷达点目标成像RD算法，模型参考合成孔径雷达成像算法与实现(Synthetic aperture radar point target imaging algorithm RD, model reference synthetic aperture radar imaging algorithm and implementation)

基于脆弱性的水印嵌入算法，包括水印嵌入，水印攻击等(Based on the vulnerability of the watermark embedding algorithm, including watermark embedding, watermark attacks and so on)

遥感图像融合，通过多个指标对融合图像进行评价，比较优劣。(remote sensing image fusion, through the integration of a number of indicators to evaluate images, and compared them.)

【实例简介】基于模板匹配的数字图片识别，使用opencv3进行图像处理

此代码采用正态分布变换算法NDT进行点云配准(This code uses the normal distribution transform algorithm NDT for point cloud registration)

基于粒子滤波和卡尔曼滤波的运动目标视频跟踪程序，非常强大和实用，强烈推荐学习使用。(Kalman filter based on particle filter and target video motion tracking program, very powerful and practical, it is strongly recommended to learn to use.)

初学者的游程编码，可以进行小图像的压缩，可以以此为基础进行编码和参考(RLE beginner, you can make small image compression, can be encoded as a basis and reference)

说明：  使用Harris角点检测器查找特征。再使用SIFT描述符并匹配两个图像之间的特征描述符。使用RANSAC执行单应。最后把图像包起来缝合。(Use Harris corner detector to find features. Sift descriptors are then used to match the feature descriptors between the two images. Use RANSAC to perform single response. Finally, the image is wrapped and stitched.)