chazhi

用C charp编写的图像滤镜效果，包括源代码。(Image filter effects)

这是基于图论的图像分割源代码，效果很好，欢迎下载.(This is based on graph theory image segmentation source code, works well, welcome to download.)

织物疵点检测和识别系统.采用2中方法，有gui界面，支持实际纺织物的检测(Fabric defect detection and identification systems. Using 2 methods, gui interface, support for the detection of the actual textile)

一个自由、开源的图形库--FreeImage3.92最新版的中文参考(支持位图构件―例如调色板和数据位―的便易访问；将位图从一种位深度转换到另一种位深度；当有多幅位图页―例如TIFF―时访问位图的不同页；基本的位图处理，如旋转、翻转（flipping）和重采样，或点操作，如亮度和对比度调整；Alpha混合与合成（Compositing and blending）；FreeImage不支持：高级图象处理操作，如回卷（Convolution）和变换（Transform）；位图绘制； 矢量图形。)(a free, revenue graphics library-- the latest version FreeImage3 .92 reference to the Chinese (support bitmap elements- such as transfer shade and data spaces- the easy access; will be from a bitmap-depth conversion to another kind of depth; When a number of bitmap page- such as TIFF- Bitmap to visit the different pages; basic bitmap processing, such as rotation, Upset (flipping) and resampling, or point operations, such as brightness and contrast adjustments; Alpha mixed with the synthetic (Compositing and blending); FreeImage not support : Advanced image processing operation, If the response (Convolution) and transform (Transform); bitmap rendering; Vector graphics.))

程序是基于DSP的数字图像处理技术，可以实现军事滤波，中值滤波和维纳滤波，实现效果较好(The program is a DSP-based digital image processing technology, the military filtering, median filtering and Wiener filtering, better )

C#实现多边形颜色的填充，主要是种子填充和种子扫描线填充两种算法。(C# implementation of the polygon fill color, mainly seeds and seed filling scan line fill two algorithms.)

k均值用于图像分割，对于相同颜色但深度不一样可以分割。(k-means for image segmentation, the same color depth can be split.)

说明：  给出了一种基于小波分形的图像有损压缩方法.首先，利用小波变换将图像分解为不同频率的分量，然后采用分形迭代函数系统、Huffman树等方法对它们进行编码.实验表明，该算法在保证还原图像质量的情况下，有较高的压缩比.(Image Compression Bassed on Wavelet and Fractal)

说明：  n个点电荷电场线的matlab仿真 分别有1个 2个等（可以通过改变程序数字来得到相应的仿真结果）(Matlab simulation of N-point charge electric field lines)

对于原始图像 < f5.tif > ，实现下列结果。 a.用平均滤波器平滑原始图像得到的模糊图像 b.用拉普拉斯算子增强上述a得到的模糊图像 c.用拉普拉斯算子增强原始图像 (For the original image <f5.tif>, to achieve the following results. a. smoothing filter with an average original image was blurred b. using Laplacian enhancement get a blurred image above c. using Laplacian enhancement of the original image)