另一种光照不均匀图像的图像增强法源代码，编译通过，效果良好...

图像处理方面非常有用的工具，可用在多种环境下-OpenCV，Image Processing

几个常用图像处理程序源码，vc 6.0 sp6+windows2000 sp4调试通过-several commonly used image-processing program source code, vc 6.0 SP6 windows2000 Explorer debugging through

canny算子的vc源代码，可以很好的理解canny算子的原理-canny operator vc source code, can be a very good understanding of the principles of canny operator

C下gabor滤波算法 提取图象纹理特征的经典方法 under C filtering algorithm extract image texture features one of the classic methods -C under the gabor filtering algorithm extracted image texture features classic method under C filtering algorithm extract image texture features one of the classic methods

这个是彩色图像分割方法。与RegionExtract采用的方法不同。 首先rgb转换成hsv，对h分量进行直方图分割，得到直方图的峰值和峰谷。利用得到的峰值和峰谷进行区域分割，这样会得到很多的小区域，对这些小区域进行区域合并，区域合并的终止条件是：区域一致性距离在某个固定的阀值之间，比如20或者在某个自适应阀值（该阀值自动计算）。注意：区域合并在luv空间进行。-This is a method for color image segmentation. With the different methods used RegionExtract. First rgb convert hsv, components of the h histogram segmentation, the histogram peak and peak and valley. Utilization of the peak and peak-valley regional partition, it would receive many of the small area of these small regional regional merger, regional merger termination conditions are: the regional consistency of the distance between a fixed threshold, such as 20 or in a self-adaptive threshold (the threshold automatically calculated). Note: regional merger in luv space.

使用log-Gabor滤波器对图像进行滤波程序。-The use of log-Gabor filter image filtering process.

编辑处理图片的delphi源码，含有典型的几种图片处理编辑代码-Editing pictures delphi source, containing several typical image processing editing code

图像处理初步，包括线性变换，几何变换，边缘检测-Preliminary image processing, including linear transformations, geometric transformations, edge detection

VC++ MFC编的数字图像处理程序源代码 包括图像反转 模板卷积 中值滤波等 由于时间有限为全部完成 希望大家在源程序上基础上添加程序 进一步增加程序功能-Image Processing1.0

基于kmeans的图像分割算法，首先得到图像，再确定分类，并计算各分类的均值，从而得到各个像素的分类。-Kmeans-based image segmentation algorithm, first of all get the image, and then determine the classification, and calculate the various categories mean, and thus obtain the classification of each pixel.