V4L2

说明：  模板匹配的一个matlab实例，程序可读性好。(template matching a Matlab example, procedures readable.)

利用多尺度高斯函数去除场景的光照分量；然后构造了一种二维伽马函数，利用光照分量的分布特性调整二维伽马函数的参数，降低光照过强区域的亮度值，提高光照过暗区域的亮度值，最终实现对光照不均匀图像的自适应校正处理。(The multi scale Gauss function is used to remove the illumination component of the scene, and then a two-dimensional gamma function is constructed. The parameters of the two-dimensional gamma function are adjusted by the distribution characteristics of the illumination component, the brightness value of the light illuminated region is reduced and the brightness value of the light dark area is improved. Finally, the adaptive correction of the uneven illumination image is realized. Positive treatment.)

鼠标写毛笔字源码例程，程序结合易语言扩展界面支持库和图像格式转换支持库，实现用鼠标写出毛笔字的效果。可以展现多种毛笔字形态，启动时有使用帮助说明。(Mouse calligraphy source routines, programs combined with easy language support library expansion interface and image format conversion support library , use the mouse to write calligraphy achieve results. )

方向检测的粒子滤波程序，内含重采样算法。(The direction of the particle filter detection procedures, including re-sampling algorithm.)

实现了图像的加水印，去噪，加噪声等功能，基于kaiser窗的双谱线插值FFT谐波分析，用于建立主成分分析模型。( Realize image watermarking, de-noising, plus noise and other functions, Dual-line interpolation FFT harmonic analysis kaiser windows, Principal component analysis model for establishing.)

实现图像的旋转，根据旋转矩阵进行旋转,并对结果进行调整(rotate picture)

实现ICM算法（条件迭代模型）对于灰度图像的分割(Achieve ICM algorithm (iterative model conditions) for the gray-scale image segmentation)

基于分片重排列技术的维数约简方法，用于特征提取。(Patch Alignment for Dimensionality Reduction，IEEETrans.，2009.)

Efficient Computation of Shortest Paths in Networks Using Particle Swarm Optimization and Noising Metaheuristics

极化SAR图像Four component 目标分解结果，使用数据为Flevoland地区部分数据，可用于极化SAR图像分类(Four component decomposition result of PolSAR image, the used dataset is the subarea of Flevoland region, it can be used as the classification features for PolSAR image classification.)