finalblock

用matlab实现了图像通信中的全搜索算法与三步搜索算法这两种运动估值算法，给出了运动矢量图，对两种方法的计算复杂度和搜索性能进行了客观的比较。(Matlab image communication achieved by the full search algorithm in the three-step search algorithm with the two motion estimation algorithms, given the movement vector, the computational complexity of both methods and the search performance of objective comparison.)

说明：  Ostu分割方法实现 根据原理编写Ostu程序，对cameraman灰度图片进行分割；并对获得的前景与背景，分别再进行一次分割；(Implementation of Ostu segmentation method According to the principle, the Ostu program is compiled to segment the gray image of cameraman, and the foreground and background are segmented again;)

对图像进行傅立叶变换和反变换，计算频谱幅值(The image Fourier transform and inverse transform, the amplitude spectrum is calculated)

php图像处理，用php实现，进行简单的操作，编辑，修改等功能(Intervention Image is a PHP image handling and manipulation library providing an easier and expressive way to create, edit, and compose images. The package includes ServiceProviders and Facades for easy Laravel integration.)

中值滤波在图像处理中占据很重要的地位，本代码是加权中值滤波处理源码。希望对大家有用。(Median filter in image processing occupies a very important position, the code is weighted median filter processing source. Hope to be useful.)

2012实习，新鲜的matlab实现水印的嵌入和提取，包括盲水印提取代码(watermark embedding and extraction, including the blind watermark extraction code)

图像检测的算法，Faster R-CNN算法，先对整张图像进行卷积计算，然后通过感兴趣区域池化层(RoI Pooling Layer)将选择性搜索算法推荐出来的候选区域和卷积网络计算出的特征映射图进行融合，得到候选区域对应的特征矢量，这种共享卷积计算的操作极大地减少了卷积计算的次数。而且这些特征矢量的维度统一，方便后续的分类工作。通过感兴趣区域池化层处理卷积特征，并将得到的特征送往两个并行计算任务进行训练，分类和定位回归。通过这些方法和改进的框架，Fast R-CNN 用更短的训练和测试时长，取得了比 R-CNN 更好的效果(Faster R-CNN algorithm first convolutes the whole image, then fuses the candidate regions recommended by the selective search algorithm and the feature mapping maps calculated by the convolution network through the RoI Pooling Layer to get the corresponding feature vectors of the candidate regions, which greatly reduces the number of convolution calculations. Moreover, the dimension of these feature vectors is unified, which facilitates the subsequent classification work. The convolution feature is processed by the pooling layer of the region of interest, and the obtained feature is sent to two parallel computing tasks for training, classification and positioning regression. Through these methods and improved framework, Fast R-CNN uses shorter training and testing time and achieves better results than R-CNN.)

基于matlab的图像小波融合测试程序，选取四副位图文件为对比(Matlab wavelet-based image fusion test program)

USB Composit example for HID

卡尔曼滤波（扩展方法）定时定位，自己编写调试。(Kalman filter (extension methods) time positioning, write your own debugging.)