first_semester

说明：  m-map工具箱，可以帮助画图，比如世界地图的背景(M-map toolbox, can help draw pictures, such as the background of the world map)

图像配准算法打包，包括很多经典的配准算法(Image registration algorithm，include many classical registration algorithm)

首先生成如下形式的图片：图中的白条为7象素宽，210象素高，白条间的宽度为17象素。 应用多种滤波器进行处理：算术均值，几何均值，谐波均值，逆谐波均值，中值滤波，中点滤波，最大值、最小值滤波等。注意，需改变模板大小。详细比较上述的结果，并分析原因。 (First generation following form images: figure IOUs 7 pixels wide, 210 pixels high, the width is 17 pixels between IOUs. Using a variety of filters for processing: the arithmetic mean, geometric mean, harmonic mean, inverse harmonic mean, median filtering, filtering midpoint, maximum, minimum filtering. Note that the need to change the template size. A detailed comparison of these results and analyze the reasons.)

四叉树分割 opencv 编写 读入灰度图 进行递归分割(Quadtree segmentation opencv read into grayscale prepared for recursive partitioning)

分别利用均值滤波、自适应滤波和中值滤波对噪声图像g1和g2进行滤波，利用峰值信噪比对去噪性能进行比较。(Respectively, using the mean filter, adaptive filtering and median filtering images g1 and g2 noise filtering, denoising performance comparison using the peak signal-to-noise ratio.)

深度学习相关代码实现，可以用来做去噪，去模糊，回归，识别等( Initialize and train an RBM energy-based model. Supports binary, Gaussian, and multinomial inputs (still in development). Supports binary and noisy rectified linear units (NReLU) in the hidden layer. Supports joint modeling of binary and multinomial variables for classification.)

去噪，一个非常好的去噪源代码，简单好用，设置方便(Denoising, denoising source code is a very good, easy to use and easy set up)

基于MATLAB平台下，可获取图片任意点的像素坐标。(Based on MATLAB platform, the pixel coordinates of any point in the picture can be obtained.)

一份关于用正则化去除图像模糊的资料，内含代码以及说明，并附上了仿真结果图(A report on the Regularization blur removal image data containing codes and descriptions, along with the simulation results of FIG.)

多类图像特征结合上下文信息进行目标识别（分类、分割）(Many types of image features combined with context information for target identification (classification, segmentation))