total8bian

傅里叶变换的基本概念介绍和应用，做计算和频谱分析时蛮有用的。(fourier transform)

说明：  利用97小波变换进行图像压缩，用matlab仿真，实验证明它具有较高的压缩比(using wavelet transform image compression using Matlab simulation experiment to prove that it has a higher compression ratio)

说明：  图像处理程序，基于K均值聚类的图像分割——灰度图像，基于中位数算法的运动目标检测(Image processing program, image segmentation based on k-means clustering -- gray image, moving target detection based on median algorithm)

MKL多核学习综述文章对应的很多MKL代码的合集，里面有很多有代表性的代码，非常详细！(MKL multicore learn many review articles MKL code corresponding collection, there are a lot of representative code, very detailed!)

用matlab写的sift算法的全过程，用于提取特征点，是图像识别的一种好算法(The algrithm of sift)

包括canny，sobel，log等边缘检测的改进算法，使用效果良好(Including improved edge detection algorithms such as canny, sobel, log and so on, the application effect is good.)

ENVI二次开发常用功能代码，包括大气校正、定标、分类(监督+非监督)、裁剪、镶嵌等(ENVI secondary development commonly used function codes, including atmospheric calibration, calibration, classification (supervision+ unsupervised), cutting, mosaic, etc.)

说明：  Matlab编写的程序代码，包括基于肤色的人脸检测，根据人脸图像判别眼睛的状态（睁眼及闭眼）(Matlab program written in code, including color-based face detection, face image in accordance with the state of discriminant eyes (eyes open and eyes closed))

利用双线性插值和最近邻插值实现RGB图像的缩放，利用MATLAB编写(The use of bilinear interpolation and nearest neighbor interpolation to achieve RGB image scaling, using MATLAB to prepare)

：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相结合的方法对叶片多特征进行特征降维，将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量 机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)