tong311

基于粒子滤波的视频目标跟踪算法matlab源程序，内涵视频文件及算法源程序。(Video object tracking algorithm based on particle filter matlab source program, content video files and algorithm source program.)

用于图像处理上的像素点之间相关性的计算，主要用于分析像素值之间的关联度。(For the calculation of the correlation between the pixels on the image processing)

VC++图像平滑处理+程序源码，实现图象的平滑（去噪声），锐化功能，测试时请在C盘下放一个测试用的Bmp图片，路径：C: est.bmp，没有的话没法测试。如上图所示是水平平滑处理，可以对比下，不过感觉颜色失真了，有兴趣的看一下。命令行编译过程如下： 　　vcvars32 　　rc bmp.rc 　　cl smooth.c bmp.res user32.lib gdi32.lib(VC++ image smoothing+ program source code, to achieve a smooth image (to noise), sharpening function in the C drive when testing a test of decentralization Bmp picture, path: C: test.bmp, no words can not test . Is shown above the level of smoothing, you can compare the next, but the feeling of color distortion, interested look. Command-line compiler as follows: vcvars32 rc bmp.rc cl smooth.c bmp.res user32.lib gdi32.lib)

说明：  给出了一种基于小波分形的图像有损压缩方法.首先，利用小波变换将图像分解为不同频率的分量，然后采用分形迭代函数系统、Huffman树等方法对它们进行编码.实验表明，该算法在保证还原图像质量的情况下，有较高的压缩比.(Image Compression Bassed on Wavelet and Fractal)

基于暗原色的雾天图像清晰化算法研究,系转载，如有雷同，概不负责(Algorithm based on the clear image of dark primary colors fog)

一段matlab试验程序，可以学习FFT+降噪的功能，适合初学者。(Test a matlab program, you can learn FFT+ noise reduction features, suitable for beginners.)

beginig : image processing using LENA_color

双目立体视觉，采用两张图像恢复三维形状，外国人的一个开源项目。(System Prototype to make 3D reconstruction solution using stereo images. It works with common cameras and not require large amount of memory during the images processing. It provides a low cost solution to educational environments with low budgets. )

Visual Geometry Group项目组开发的超分辨率重建的源码，具有很好的效果。 附有详细的文档说明，可直接运行(a good super-resolution reconstruct source code developed by Visual Geometry Group, with detail description)

分为行人检测，特征提取，行人跟踪三步，其中最主要的代码也是这个代码的中心是行人跟踪这一部分，我采用的是kalman滤波器进行行人下一帧位置的预测，可以很好的提高行人跟踪的鲁棒性，跟踪结果比较准确。(Into pedestrian detection, feature extraction, pedestrian tracking steps, which is the center of the main code of the code is pedestrian tracking this section, I kalman filter is used to predict the position of the next frame pedestrians, can be a good improvement pedestrian tracking robustness, tracking results more accurate.)