可以对图像进行纹理分析，已经调试通过，效果较好，对需要纹理特征提取的朋友很有用。...

经典书籍-数字图像处理-冈萨雷斯。解决各位敲代码的烦恼！These MATLAB functions were created for the book Digital Image Processing Using MATLAB (DIPUM), by R.C. Gonzalez, R.E. Woods, and S.L. Eddins, Prentice Ha-Classic books- digital image processing- Gonzalez. To resolve the trouble code you knock! These MATLAB functions were created for the book Digital ImageProcessing Using MATLAB (DIPUM), by RC Gonzalez, RE Woods, andS.L. Eddins, Prentice Ha

Canny边缘检测算法,canny算法计算梯度,并从小波模极大重构图像.-Canny edge detection algorithm, canny algorithm for calculating the gradient, and from the Wavelet Modulus Maxima Image Reconstruction.

反色：通过对图像的处理使图像各种颜色变得和原始图像颜色相反-Anti-color: image processing of the image has become a variety of colors and the original image color contrast

改进的水平集方法，采用C_V模型进化。为多相位-improve the level set method, C_V evolutionary model. For the multi-phase

通过分类器自动识别图像中的人脸-Automatic recognition through classifier human face images

有关目标跟踪的11篇IEEE文献 对理解目标跟踪领域，学习检测、分类、跟踪以及后期的图像理解有很大帮助 希望能帮助更多的人-Tracking the target 11 IEEE literature in understanding the field of target tracking to study detection, classification, tracking and understanding of the late images of great help to help more people

运动目标检测中背景差分法和时间差分法的实现结构包括平台。

PixelFusion工程实现图像融合,PixelFusion工程程序运行时，用户须载入两幅图片，其中全色图像选择给定的图片spot.bmp， 而多光谱图片则为给定的图片tm.bmp。而后用户便可选择各种融合算法进行融合处理。-PixelFusion works to achieve image fusion, PixelFusion project is running, users have to load two images, one full color image to choose a given picture spot.bmp, and multi-spectral images for a given picture tm.bmp. Then the user can choose a variety of fusion algorithm fusion treatment.

将TV信号转换到VGA信号，通过FPGA的转换可以直接在显示器上显示。-TV signals will switch to VGA signal, through the FPGA conversion can be directly displayed on the monitor.

一种基于相位的光流计算方法，该方法不同于以往基于微分的计算方法，而是采用空间滤波器，取得非常好的效果。该结果发表于IEEE Trans. Neural Networks,13(5), 1127--1136. -Gautama, T. and Van Hulle, M.M. (2002). A Phase-based Approach to the Estimation of the Optical Flow Field Using Spatial Filtering, IEEE Trans. Neural Networks, 13(5), 1127--1136.