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...

高效的图像增强算法，速度快，效果好！欢迎相互交流！-Efficient image enhancement algorithm, fast, good effect! Welcome to exchange!

Artificial Immune Systems tutorial presentation,人工免疫算法，需要的通知可以学习-Artificial Immune Systems tutorial prese ntation, artificial immune algorithm, the notice can learn

求两个多边形交集的程序，使用计算几何实现的，值得学习-intersection of polygons for the two procedures, the use of computational geometry to achieve, and worth learning

本代码用于处理图像增强，主要用VC++语言完成-Image enhancement

各种各样的非压缩图像格式（bmp,ppm,pgm）转化源码。-variety of non-compressed image formats (bmp, ppm, pgm) into the source code.

png文件的读取程序和例子程序，简单方便。-png read the document procedures and examples of procedures simple and convenient.

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.

直方图均衡化的实例，大家在对图像对比度增强时必须得用到的经典程序，VC实现，简单易用，带图片可测试。-histogram equalization example, everyone in the image contrast enhancement to be used in the classic procedure, VC, simple and easy to be tested with pictures.

图象的几何变换 打开一幅位图，实现几何变换 命令行编译过程如下 vcvars32 rc bmp.rc cl geotrans.c bmp.res user32.lib gdi32.lib-Images of geometric transformations to open a bitmap, geometric transformations realize the process of command-line compiler is as follows vcvars32rc bmp.rccl geotrans.c bmp.res user32.lib gdi32.lib

高斯随机噪音程序，做理论模型数据时，一般会加高斯随机噪音，以模拟实际数据-Gaussian random noise process, make the theoretical model data, they generally will be Gaussian random noise to simulate the actual data