主要是介绍opencv的参考手册及其包括的一些其他的相关的参考手册函数，另外还有些相关典型的程序...

一种基于walsh变换的图像立体匹配方法，获得了较好的效果，具有较强的抗噪声性能 -Walsh transform based image stereo matching method to obtain good results, with strong anti-noise performance

JPEG解码程序，包括BASELINE 和 PROGRESSIVE 两种常用格式。-JPEG decoding procedures, including BASELINE and PROGRESSIVE two common format.

本书为川大的朱允民教授的《multisenor_decision_and_fusion》一书，供有关人员下载-The book for the Sichuan University Professor Zhu Yunmin of the

此程序利用3X3拉普拉斯模板增强灰度图像-procedures for the use of this template 3X3 Laplace enhanced gray image

用canny算子提取边缘，核心：用高斯滤波器平滑图像；一阶偏导的有限差分计算梯度的幅值和方向；非极大值抑制；双阈值算法检测和连接边缘。

基于小波的ICA-R算法，适合混合图像的分离。具有速度快等优势。-Wavelet-based ICA-R algorithm, suitable for the separation of mixed images. With a speed advantage.

hough变换的一些经典文章，可供参考。-hough transform a number of articles for reference.

本代码实现的功能：24位位图（BMP）的灰度化。具体实现过程：打开图像文件,找到数据区(每3个字节代表一个象素的R,G,B值),循环扫描,根据RGB的权重,计算出灰度值. 如果要得到256色灰度图,则要新建一个调色板,修改信息头和文件头.-Realize the function of the code: 24-bit bitmap (BMP) of the gray. Concrete realization of the process: Open the image file, locate the data area (3 bytes per pixel on behalf of a R, G, B values), cyclic scan, according to the weight of RGB, gray value is calculated. If you want to get 256 colors grayscale, would create a new palette, modify the header and file header information.

这是类似photoshop的灰度图算法。经计算很接近photoshop。可以用于很多图像处理算法。-This is similar to the grayscale algorithm photoshop. Calculated is very close to photoshop. Can be used in many image processing algorithms.

实现简单图像处理，包括256色转灰度图、Hough变换、Walsh变换、中值滤波、二值化变换、亮度增减、傅立叶变换、反色、取对数、取指数、图像平移、图像旋转、图像细化、图像缩放、图像镜像、均值滤波、对比度拉伸、拉普拉斯锐化（边缘检测）、方块编码、梯度锐化、灰度均衡、直方图均衡、离散余弦变换、维纳滤波处理、逆滤波处理、阈值变换、高斯平滑。-simple image processing, including color to grayscale 256, the Hough transform, Walsh transform, Median filtering, binary conversion, brightness changes, Fourier transform, and color-from the few to admit index, image shifting, image rotation, refined images, image scaling, image mirroring, mean filtering, contrast stretching, Laplacian sharpening (edge detection), block codes, Sharpening gradient, gray balance, histogram equalization, discrete cosine transform, Wiener filter, reverse filtering, threshold transform, Gaussian smoothing.