fusion

改进经典的otsu算法，使其适应目标所占图像比例较小的情况，使图像分割方法更具有自适应性 (Improve classic otsu algorithm to achieve image segmentation)

基于Harris角点检测的图像拼接matlab实现， 主要内容包括Harris角点检测，NCC,RANSAC以及2幅图像的拼接(A image mosaicing algorithem which based on Harris corner feature detection achieved in matlab. The main contents include the Harris corner detector, the NCC, the RANSAC and two image mosaicing)

说明：  基本卡尔曼滤波算法，用于目标跟踪，适用于毕业论文设计及工程人员参考 这个比较简单 易懂(The basic Kalman filter algorithm for target tracking, for design and engineering thesis is simple and easy to understand this reference)

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)

谱残缺算法显著性检测源程序!!谱残缺算法显著性检测源程序!!(the vision of matlab of special residual of salienp)

一些常见的图像处理方面的图像（尺寸不一）(Some common image processing aspects (different sizes))

用于压缩感知重构的TV算法,主要解决压缩感知中图像重构的问题(Used to compress TV algorithm to reconstruct the perception)

提出了一种针对复杂环境下的过人脸检测方法，首先在CbCgCr空间利用直接最小二乘法构建了对光照和复杂背景鲁棒性更好肤色聚类模型，实现了准确的肤色检测；然后针对人脸中姿态和表情变化，提出了基于Adaboost的多姿态人脸检测，精确的实现了人脸检测定位。(Extraordinary face detection method for complex environments, the first space CbCgCr ​ ​ direct least squares method to build a better robustness to light and complex background color clustering model to achieve accurate color detection forface, posture and facial expression changes, proposed the multi-pose face detection based on Adaboost, accurate face detection and location. )

本算法在Matlab2008b 环境下实现。包括main,san 和ssd 三个函数。 这次实现的算法并不是比较两个已经知道的点是否匹配，而是已知一个图形中的特征点，在另外一个图像中找到与其最匹配的点，匹配度用SAD 或者SSD 来度量。 main.m 是程序的入口，包括生成和读入实验数据，调用sad 函数和ssd 函数求匹配点，最后绘 制出最后的结果。sad.m 是用sad 度量方法在另一图中求解匹配点的函数实现，有3 个参数 y=sad(x,image1,image2)。其中x 是代匹配的数据，image1 是图像1 数据，image2 是图像2 数据。 从理论上分析，ssd 比sad 算法要复杂一点，经过测试，在一幅640*480 的图像中寻找10 个匹配点数据SAD 用时25.062519 秒，SSD 用时25.291432 秒。(The algorithm Matlab2008b environment to achieve. Including the main, san, and ssd three functions. The implementation of the algorithm is not the point of comparing two matches already know, but the known feature points in a graphic, an image found in the other match with the most points, matching measured with the SAD or SSD. main.m is the entry, including the generation and reading test data, call the sad ssd function evaluation functions and matching points, and finally draw the final result. sad.m measure is sad figure in another match point in the function implementation to solve, there are three parameters y = sad (x, image1, image2). Where x is the generation of matching data, image1 is the data image 1, image2 is the image 2 data. From the theoretical analysis, ssd little more complicated than the sad algorithm, tested in a 640* 480 images of 10 match points in the search for data using time 25.062519 seconds SAD, SSD with time 25.291432 seconds. )

1.DCT变换，对整个图像的直接DCT变换和分块为8*8做DCT变换，并设定阈值。 2.汉明编码（7，4），译码以及找出错误图样和纠错。并在不同的转移概率的BSC道下进行传输。(DCT:Direct DCT and IDCT,blocking. hamming coding:decoding and picking up errors.)