4.image-fusion-algorithm

说明：  基于小波变换的数字水印嵌入程序（将二值图像嵌入尺寸相同的灰度图象中）(based on wavelet transform digital watermark embedding process (will embed binary images the same size as the gray image))

图像处理包括图像的各种变换、阈值分割、边缘提取、边缘跟踪等等很多处理的源代码,可以正常运行(Image processing includes a variety of transformed image threshold segmentation, edge detection, edge tracking and so many of the source code, you can normally run)

％通过耦合神经网络结合中值滤波实现图像的降噪源代码( Through the combination of coupled neural network filtering image noise source code)

实现非均匀傅里叶变换代码，可用于石油地震勘探、航空航天、图像处理，电子电工方向。(Achieve non-uniform Fourier Transform code, can be used for seismic exploration, aerospace, image processing, electronics and electric direction.)

手机壁纸截图小工具源码程序，结合易语言扩展界面支持库，应用易语言图像格式转换支持库，可以截取指定格式的图片，用于手机壁纸。(Phone wallpaper theme gadget source program, combined with easy language support library expansion interface , the application image format conversion easy language support library , can intercept a specified format pictures, wallpaper for mobile phones .)

分段自适应正交匹配追踪StOMP算法源程序，压缩感知里面很好的算法(Orthogonal Matching Pursuit StOMP adaptive segmentation algorithm source code, a good algorithm inside compressed sensing)

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.)

说明：  两种基于非下采样变换图像去噪方法，效果比contourlet变换要好(Two transform based image denoising nonsubsampled method, the effect is better than contourlet transform)

标准单纯性算法程序,不知能否满足大家需要,()

说明：  水下图像处理方法之一的图像融合算法matlab实现(Matlab implementation of image fusion algorithm, one of the classical image processing methods)