读写进行实验，对初学者理解遥感图像…

1>图像处理系列之一－－读写篇 涵盖内容： 1>图像处理简介 2>常用图像文件格式说明 3>BMP图像文件读写 涉及VC知识主要有： 1>消息添加 2>文件读写 3>串行化 实验环境： Win+VC6.0 实验图片在Imagetest子目录下Data文件夹中.-1

retinex算法的C语言代码实现，用于图象处理-Retinex algorithm realize the C language code for the image processing

实现计算机图形学中的光线跟踪算法，有整个demo系统，用户可以将函数Trace单独使用-of ray tracing algorithms, the demo system as a whole, will allow users to use a separate function Trace

基于图像处理的相机自动调焦系统-camera auto focus system based on image manipulating

基于ISE的DPRAM进行并行和串行的数据格式转换。-use for the ISE DPRAM IP to do with form parallel data format to serial fromat process.

挖图小程序。。。。。。。C++编写。。VC开发环境-dug a small procedure. . . . . . . C preparation. . VC development environment.

一个小图像非法反动的大幅度反对反对反对反对反对反对非法反动反对反对反对反对反对反对反对反对非法大幅度反对方-啊随时随地 方法份额份额份额反反复复份额份额份额呃呃呃份额发

The transformation parameters are specified by the user by editing the values of the rotation, scale (x and y), and shear (x and y). The translation is not icluded because it can be easily (normalized or) removed from the image by subtracting the shape cetroid. The affine matrix and the affinr transformation are computed using Matlab Image Processing Toolbox functions: maketform and imtransform. So this program is only demonstrates and facilitates the computation and the applying of these functions to a 2-D image. -The transformation parameters are specified by the user by editing the values of the rotation, scale (x and y), and shear (x and y). The translation is not icluded because it can be easily (normalized or) removed from the image by subtracting the shape cetroid. The affine matrix and the affinr transformation are computed using Matlab Image Processing Toolbox functions: maketform and imtransform. So this program is only demonstrates and facilitates the computat

图像处理，用于图像增强，亮度改变，可以增强图像的清晰度！-Image processing for image enhancement, brightness change, it can enhance image clarity!

可实现与graph-cuts算法相似的图像分割效果. 他借用了生物形态学知识，将每一个像素视为一个细胞，这些细胞可能是前景，背景，或其他。这些细胞依据其灰度竞争获得生长，由此获得分割。-This algorithm is presented as an alternative to graph-cuts. The operation is very simple, and can be thought of with a biological metaphor: Imagine each image pixel is a "cell" of a certain type. These cells can be foreground, background, undefined, or others. As the algorithm proceeds, these cells compete to dominate the image domain. The ability of the cells to spread is related to the image pixel intensity