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针对分水岭算法存在的过分割问题以及VCH-F1切片图像的特点，提出一种能够有效消除局部极小值和噪声干扰的自动分割方法。首先比较彩色分量梯度图，选择分量图像的梯度信息，达到有效提取图像边缘信息的目的；然后提出基于多阈值分割的方法消除无效梯度信息；最后介绍了算法的步骤及结果。实验结果证明，通过该方法处理的梯度图像再进行分水岭算法处理，即使不进行区域合并也能达到很好的效果。(Watershed algorithm for over-segmentation problem of the existence of VCH-F1 as well as the characteristics of the image slice, a can effectively eliminate the local minimum value and noise automatic segmentation method. Comparing the first color component gradient map, select the quantity of image gradient information, achieve an effective extraction of image edge information purposes then made based on multi-threshold segmentation method to eliminate invalid gradient information Finally introduce the steps of the algorithm and results. Experimental results show that the adoption of the method of treatment of gradient watershed algorithm for image re-treatment, even if there is no regional merger will also achieve good results.)

蚁群算法，图像边缘检测，用于模式识别，可以编译通过！(Ant colony algorithm for image edge detection for pattern recognition can be compiled by!)

说明：  包括几种基于多项式插值的图像处理matlab代码，包括双三次插值，样条差值等(Includes several image processing based on polynomial interpolation matlab code, including double-cubic interpolation, spline difference, etc.)

对图像进行边缘检测的程序，实例为经典的lena图像。(The image edge detection procedures, examples of classic lena image.)

基于AM-FM纹理模型的图像特征提取方法研究(AM-FM texture model-based image feature extraction method)

自适应模板更新的粒子滤波实时跟踪算法_赖作镁.zip(Adaptive template updating particle filter for real-time tracking algorithm _ Ryan magnesium. Zip)

这个程序可以用于两个图像的拼接，通过寻找特征点完成拼接(This program can be used to stitch two images and complete the stitching by finding feature points.)

本压缩文件利用Matlab制作了一个能识别居民身份证号码的系统，使用图像处理技术，实现了计算机识别数字的功能。(The compressed file using the Matlab made a system can identify the identity card number, using image processing technology, realized the function of the digital computer identification. )

这是一个基于vc++语言下读取像素点灰度值(write highhui of a photo!)

几幅SAR图像。对SAR图像处理的童鞋很有用的。(Pieces of SAR images. Of SAR image processing is useful for students.)