danfu

说明：  虚拟示波器实现示波器的功能 数据采集 处理 存储(Virtual oscilloscope)

遥感图像分类描述，有代码，也有图像，用Matlab实现(Remote sensing image classification description, code, there are images, achieved with the Matlab)

自己编的特征选择程序，分别包括用顺序前进法(SFS),顺序后退法(SBS),增l 减r 法(l–r)、SFFS法进行选择的程序(own addendum to the feature selection procedures, including the use of sequential forward (SFS). back order (SBS), by reducing r l (l-r), SFFS method to choose the procedure)

对于图像图形处理，基于先验形状、窄带法的CV模型的分割方法，有举例说明，效果明显。(For image and graphics processing, segmentation method based on a priori shape, Narrow Band CV model, there are illustrated, the effect is obvious.)

稀疏自适应匹配追踪算法，无需稀疏度，就可以重构原始信号。(Sparse adaptive matching pursuit algorithm, without sparsity, we can reconstruct the original signal.)

针对多聚焦图像融合，本文首先介绍了小波变换融合算法，虽然小波变换方法无冗余，高频分量损失较小，具有较好的融合效果，但存在两个主要缺点：一是移变性，二是融合图像在重构时会受到一些外来因素的影响，所以仍会丢失一些边缘信息，为了克服小波变换法的以上缺点，可以采用基于小波分解和点扩展函数模型PSF相结合的融合方法。该方法首先对不同的图像进行无降2采样的小波分解，以保持与源图像大小相同，然后分别将其各方向、各尺度的高频分量进行叠加，并依此提取其高频分量的特征信息来判定清晰目标或模糊目标，以此来设计融合算法，采用一定的策略将两副源图像进行融合，从而避开了小波的反变换，因此融合后的图像具有比小波变换法更好的融合效果。(multi-focus image fusion, this paper introduces the wavelet transform algorithm, Although the wavelet transform non-redundant, the loss of high-frequency components are smaller, better integration effect, But there are two major drawbacks : First, the shift variability and the second is the integration of image reconstruction will be subject to a number of external factors. Therefore, there would still be some marginal loss of information, in order to overcome the wavelet transform of the above shortcomings, can be used based on wavelet decomposition and the point spread function PSF model combining the fusion method. The first pair of different images ratchet two sampling wavelet decomposition, and to maintain the same source image size. Then all of its direction, the scale of high-freque)

数字图像相位相关性，对两幅图像位移的前后相位变化进行检测(Phase Correlation)

全息图的建立与重现 比较简单 但是有说明 比较容易懂(The establishment and reproduce hologram is relatively simple but relatively easy to understand instructions)

用fibonacci变换方法对图象做置乱或逆置乱，效率极高，在信息隐藏中属常用的方法之一。调用函数为f=fibonacci_t(I,r,s)，其中参数分别为I=被置乱的图像，r=置乱密钥，s=0置乱，s=1逆置乱(Fibonacci transformation method used to do on the image or inverse Scrambling Scrambling, high efficiency in the information hidden in one of the methods are commonly used. Call the function f = fibonacci_t (I, r, s), which parameters were I = have been scrambling the image, r = scrambling key, s = 0 Scrambling, s = 1 inverse Scrambling)

bag of words 图像识别算法，斯坦福大学李飞飞实验室做的demo(bag of words)