exp_2_1

说明：  李春明于2005年提出的CLIC，一种对MR图像偏移场矫正方法(Li Chunming's CLIC in 2005, an offset correction method for MR images.)

本代码是描述图像融合的一个综合性代码，其中包括对图像变换提升等一系列试验方案(The code is described in an integrated image fusion of code, including the transformation of images, such as a series of pilot programs to enhance)

先用PCA降维，在利用支持向量机进行分类，这个分类是二分类，所以PCA的降维降到两维即可分类。(Firstly, PCA dimensionality reduction is used to conduct classification with support vector machine. This classification is binary classification, so the dimensionality reduction of PCA can be reduced to two dimensions for classification.)

这个文件用PCD算法解决压缩感知（构造一个冗余字典用于图像的修复）(Using PCD algorithm to solve compressed sensing (constructing a redundant dictionary for image restoration).)

sar 图像定标程序，由灰度值计算后向散射系数(sar image calibration)

本系统实现指纹的识别和差异比对，通过差值程度来反映相似程度。(The system realizes fingerprint identification and difference alignment, and reflects the similarity degree by the degree of difference.)

只能信息树立的相关课件和Matlab源代码，对于学习只能信息处理的学员很有帮助。(Information can only be set by the relevant courseware and Matlab source code, for students to study information processing can only be helpful.)

说明：  这是一篇关于大气湍流退化图像复原的硕士论文，我用matlab对该论文中阐述的方法进行了仿真(This is a master's thesis on the restoration of atmospheric turbulence degraded images. I used Matlab to simulate the methods described in this paper.)

说明：  分水岭算法是一种图像区域分割法，在分割的过程中，它会把跟临近像素间的相似性作为重要的参考依据，从而将在空间位置上相近并且灰度值相近的像素点互相连接起来构成一个封闭的轮廓，封闭性是分水岭算法的一个重要特征。本示例适用于二维和三维图像，计算分水岭变换并将结果标签矩阵显示为RGB图像。 分水岭算法是一种图像区域分割法，在分割的过程中，它会把跟临近像素间的相似性作为重要的参考依据，从而将在空间位置上相近并且灰度值相近的像素点互相连接起来构成一个封闭的轮廓，封闭性是分水岭算法的一个重要特征。本示例适用于二维和三维图像，计算分水岭变换并将结果标签矩阵显示为RGB图像。(The watershed algorithm is an image region segmentation method. In the segmentation process, it will use the similarity with neighboring pixels as an important reference basis, so as to connect pixels that are close in space and have similar gray values to each other. Forming a closed contour, closedness is an important feature of the watershed algorithm. This example applies to 2D and 3D images, calculates the watershed transformation and displays the resulting label matrix as an RGB image.)

说明：  自己实现的BM3D图像去噪算法。它首先把图像分成一定大小的块，根据图像块之间的相似性，把具有相似结构的二维图像块组合在一起形成三维数组，然后用联合滤波的方法对这些三维数组进行处理，最后，通过逆变换，把处理后的结果返回到原图像中，从而得到去噪后的图像。(Image Denosing by Sparse 3-D Transform-Domain Collaborative Filtering.)