JPEG2000

彩色图像处理，RGB分通道彩色显示，灰度显示，直方图均衡，假彩色图像合成(Color image processing, RGB color display sub-channel, grayscale display, histogram equalization, false color image synthesis)

strtok(char s[], const char *delim) 用来将字符串分割成一个个片段。参数s指向欲分割的字符串，参数delim则为分割字符串中包含的所有字符。当strtok()在参数s的字符串中发现参数delim中包涵的分割字符时,则会将该字符改为

本书第一部分主要介绍机器学习基础，以及如何利用算法进行分类，并逐步介绍了多种经典的监督学习算法，如k近邻算法、朴素贝叶斯算法、Logistic回归算法、支持向量机、AdaBoost集成方法、基于树的回归算法和分类回归树（CART）算法等。第三部分则重点介绍无监督学习及其一些主要算法：k均值聚类算法、Apriori算法、FP-Growth算法。第四部分介绍了机器学习算法的一些附属工具。 全书通过精心编排的实例，切入日常工作任务，摒弃学术化语言，利用高效的可复用Python代码来阐释如何处理统计数据，进行数据分析及可视化。通过各种实例，...( U672C u4E66 u7B2C u4E00 u90E8 u5206 u5206 u4E3B u8991 u4ECB u7ECD u673A u5668 u5B66 u4E60 u57FA u7840 uFF0C u4EE5 u53CA u5982 u4F55 u5229 u7528 u7B97 u6CD5 U8FDB u883C u5206 u7C7B uFF0C u5E76 u9010 u6B65 u4ECB u7ECD u4E86 u591A U90BB u6CD2 u3001 u6734 u7D2 u8D1D u53F6 u65AF u7B97 u6CD5 u3001Logistic u56DE u5F52 u7B97 u6CD5 u3001 u652F u6301 u5411 u91CF u673A u3001AdaBoost u96C6 u6210 U65B9 u6CD5 u3001 u57FA u4E8E u6811 u7R4 u5F52 u7B97 u6CD2 u5286 u5206 u7C7B u56DE u5F52 u6811 uFF08CART uFF09 u7B97 u6CD5 u7B49 u3002 u7B2C u4E09 U90E8 u5209 u5109 u91A u0312 u4E9B u8E1B u8981 u7B97 u6CD5 uFF1Ak u5747 u503C u805A u7B7B U7B97 u6CD3 u30011 by default for uppercase and uupstr U4E9B u9644 u5C5E u5DE5 u5177 u3002 u5168 u4E66 u901A u8FC7 u7CBE U5FC3 u7396 u7392 u7B09 u5B09 u5B09 u5B09 u5B03 U7528 u9184 u5R4 u5904 u7403 u7R03 u7 U5206 u6790 u53CA u53EF u89)

图像抠图是将图像的目标物体从背景图像分割出来的技术，这段代码是用MATLAB实现的一段抠图的代码(Image matting is the image of the target object from the background image segmentation techniques, this code is implemented using MATLAB code section of matting)

softcast的2d dct实现，先对图像转灰度图，得到的亮度信号矩阵做DCT 变换(softcast of 2d dct implementation, the first image to grayscale, luminance signal obtained by DCT transformation matrix do)

说明：  CUDA图像处理的程序，这个程序速度快，效率高(CUDA image processing program)

VC development motion control routines, vb development 12 axis motion control routines

基于PCNN的特征提取,PCNN用于特征提取时，具体平移、旋转、尺度、扭曲等不变性，这正是许多年来基于内容的图像检索系统追求的目标，同时PCNN用于特征提取时，有很好的抗噪性。而且PCNN直接来自于哺乳动物视觉皮层神经的研究，具有提取图像形状，纹理，边缘的属性。用PCNN能很好地对图像进行签名，将二维的图像的特征提取成一维矢量签名。(Feature extraction of specified object is an important preprocessing stage in machine vision systems. In this paper, we present a novel hybrid feature extraction method using PCNN (Pulse Coupled Neural Network) and shape information. First, we use PCNN firing map train to formulate object’s time signature, then we use roundness of each firing map to formulate object’s shape information vector, the final feature matrix we got is combined time signature and roundness. We take correlations as our judge criteria in our experiments. It has been proved that the algorithm is not sensitivity with the rotation, scaling and translation of the object and is a useful method for target recognition applications.)

Random ppm modulated analog signal under Complete class-based image processing, contains all of the source code, auto image, Correlation analysis process matlab method.

关于图像分块压缩感知，及测量矩阵加权的三篇文章(Three articles on the image block compressed sensing, and measurement matrix weighted)