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图像处理算法,实现多种对于灰度/二值图像的基本算法,包括灰度直方图,均衡化,门限处理,模糊,锐化,腐蚀,膨胀,掩模过滤,频域转换,边缘检测,梯度检测,二值化等等.实现的方法较多,且均经过一定的优化,效率不错.(Image processing algorithms to achieve a variety of for the gray/binary image of the basic algorithm, including the gray histogram, equalization, threshold treatment, blur, sharpen, corrosion, expansion, mask filter, frequency domain conversion, edge detection, gradient detection, binarization and so forth. The way to achieve more, and have to undergo a certain degree of optimization, efficiency, good.)

基于相关向量机的高光谱图像分类算法，functions中是用到的函数，另一个文件夹是主程序。(RVM hyperspectral image classification algorithm, functions are functions used, another folder is the main program.)

在matlab环境中用快速傅里叶变换实现多目标追踪，计算的非常快(Matlab environment using the fast Fourier transform to achieve multi-target tracking, very fast calculation)

说明：  多种边缘检测算子对比 不需要改动 有sobel prewittts canny log(Multiple edge detection operators)

做图像轮廓提取的应该都听说果GVF这个概念，也难免有没听过的，不过可以看看这个程序(Does the image contour extraction of GVF should have heard the concept of fruit, but also inevitably have heard, but can look at this process)

说明：  锐化图片 拉普拉斯算法 两种方法 一种是自己写的一种是用了matlab里面自带的函数(ruihua picture Laplace there are two mechof a fi [as fs aflasl;nvb)

简单的几个四叉树分解程序，主要用于图像的分割(Several simple quadtree decomposition procedure, mainly used for image segmentation)

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )

四叉树分解算法对ＲＧＢ彩色图像进行分割，ＭＡＴＬＡＢ代码，包括实验图片(Quad-tree decomposition algorithm RGB color image segmentation, MATLAB code, including test images)

Matlab源程序代码，著名的PSO程式代码，用于拟合超二次曲线，曲面的代码，适用于粒子系统。呵呵，与大家一起分享受(Matlab source code, the famous PSO program code for the quadratic curve-fitting, Surface code applicable to the particle system. Oh, and that they have enjoyed.)