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此实例已经过测试，大家拿来即可使用，无须配置！ 两个功能：一个是用程序实现下载网络图片至本地，另一个是自动生成该图片的缩略图

说明：  合成孔径雷达点目标仿真，线性变标算法（CSA），注释完整，可以直接运行，信号模型参考书目《合成孔径雷达成像算法与实现》。(Synthetic aperture radar point target simulation, linear scaling algorithm (CSA), complete annotations, can be run directly, the signal model reference bibliography "Synthetic aperture radar imaging algorithm and implementation".)

自己的小波包程序（含消噪、能量特征提取、信号重构等），希望对大家有帮助(Wavelet packet procedure (including de-noising, the energy feature extraction, signal reconstruction, etc.), we hope to help)

自适应门限二值化图像处理，自己最近完成的，还可以用，文件也加了两张图的效果，需要的可以试一试(Adaptive threshold binarization image processing, recently completed its own, but also can be used, the document also increase the effectiveness of the two plans, the needs may try it)

基于Hilbert变换的相位差测量法分析及改进 (Based on the analysis phase measurement and improvement of the Hilbert transform)

李春明 Distance Regularized Level Set Evolution and Its Application to Image Segmentation对应的分割 程序(Corresponding segmentation procedures by the the Chunming Distance Regularized the Level Set Evolution and Its Application to the Image Segmentation.)

编程实现小波的边缘检测算法，对图片的边缘处理(Edge Detection Algorithms of Wavelet Based on Programming)

提取sift特征，通过K均值聚类形成特征包，进行图像检索。(SIFT features are extracted and image packets are retrieved through K mean clustering.)

才用CDD对灰度或者彩色图像进行修复的一种方法(Only with the CDD on the grayscale or color image restoration method)

摘　要:舌象中的裂纹是中医舌诊中的重要内容。由于拍摄条件的不同,舌象质量有较大差异,传统的阈值选取方法并不 适用。文中提出一种舌象裂纹检测的自适应阈值选择方法。该方法利用舌象的L 3 a 3 b 色彩特征及区域的分裂- 合并, 对舌象进行区域分割,自适应地选取舌中部区域的色彩值作为阈值,对整个舌象进行裂纹提取。经验证,本方案对不同的 舌象能较好地提取出裂纹,实现舌象裂纹诊断的客观化。(Tongue’ s crack is a very important part of herbalist doctor diagnosis. For the different screen conditions , there are many differ2 ences on the tongue’ s quality. It is not effective to use the t raditional threshold ext raction algorithm. In order to solve this problem , pro2 pose a new adaptive threshold algorithm. Present the segmentation of the image of tongue by using the feature on tongue in the L 3 a 3 b color space and the split- combining algorithm. Then use the threshold , which is the color value ext racted automatically in the middle of the tongue , to detect the crack of the whole tongue. The experiments show that this approach is able to distill the crack effectively to different tongue images , and achieve the objectivity of the diagnosis based on the tongue’ s crack.)