slic超像素分割可更改图片位置直接使用

说明：  基于开源计算机视觉库OpenCV的图像处理基于开源计算机视觉库OpenCV的图像处理(Based on open source computer vision library OpenCV image processing based on open source computer vision library OpenCV image processing)

能够实现对生物芯片的识别和图像处理，识别有效芯片区域，读取阴性和阳性点分布和数量。(It can realize the recognition and image processing of biochip, identify the effective chip area, read the distribution and number of negative and positive points.)

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)

图像的逆滤波 维纳滤波 同时可以对图像进行模糊处理比如运动模糊 卷积模糊(Using C++ to complete images of conversion, processing and compression process, is to learn good reference digital image processing program!)

说明：  本程序主要对遥感图像实现三种处理：几何校正、图像增强和图像配准。这三种处理都可以独立实现，然而对于原始的遥感图像将这三种处理依次进行效果更佳。(This program mainly deals with three kinds of remote sensing image processing: geometric correction, image enhancement and image registration. These three kinds of processing can be realized independently, but for the original remote sensing image, the effect of these three kinds of processing in turn is better.)

图像工程作业3：基于视词袋模型的场景识别 (Scene recognition with bag of words)(Image Engineering Job 3: Scene Recognition Based visual bag of words (Scene recognition with bag of words))

利用最大熵方法求图像二值化的阈值 输入的图像名称，读取名称是M的图像文件 统计各个灰度级出现的概率 (Using the maximum entropy method for image binarization threshold input image name, the name is M read image files in various gray-scale statistical probability)

连续投影算法选出最优波段，一般是选出光谱图形的最优波段(Successive projection algorithm chooses the optimal band, typically selected spectral graph of the optimal band)

用八叉树法对逆向工程得到扫描的三维实体模型图像处理，实现了对大量点云数据进行三维网格构建。(Octree method of reverse engineering can be scanned 3D solid model of image processing, realize the construct 3D mesh of a lot of point cloud data.)

一幅大小为256×256的256级灰度图像（每像素8bit） 如果图像的各个像素之间是统计独立的，求该图像的信息熵 -离散无记忆信源 如果图像的各个像素之间不是统计独立的，求该图像的信息熵 -图像像素的概率分布模型(A 256 gray scale image (8bit per pixel) with a size of 256 x 256 If each pixel of the image is statistically independent, the information entropy of the image is calculated Discrete memoryless source If each pixel of the image is not statistically independent, the information entropy of the image is calculated Probability distribution model of image pixels)