瞳孔定位

数值实现施瓦兹-克里斯多夫变换 可将一般区域保角映射为单位圆，条形带，方形等等基本区域，包含manual. matlab源码，有GUI，可实现点、点映射的显示(Numercial realization of the Schwarz-Christoffel Conformal Mapping)

一份关于用正则化去除图像模糊的资料，内含代码以及说明，并附上了仿真结果图(A report on the Regularization blur removal image data containing codes and descriptions, along with the simulation results of FIG.)

利用SSDA算法实现模板匹配的功能，该算法可快速有效地完成图像的匹配。(SSDA algorithm on template matching function, the algorithm can quickly and efficiently complete image matching.)

基于活动轮廓模型的图像分割算法，具体算法细节，可以见压缩包中的论文(Based on Active Contour Model of image segmentation algorithm, the details of the specific algorithm, you can see the archive of papers)

合成孔径雷达目标的特征提取及其识别技术。国防科大写的！(synthetic aperture radar target feature extraction and recognition technology. Written by which this university!)

用matlab实现的霍夫曼编码的图像压缩，主要就是依据霍夫曼编码的原理实现的图形图像处理。(Using the Huffman code matlab realize the image compression, Huffman coding is mainly based on the principle realize graphics image processing.)

通过将高分辨率的图像和低分辨率的图像进行融合，来实现图像的融合。(By fusing high-resolution and low-resolution images, image fusion can be achieved.)

图像的特征用到了Dense Sift，通过Bag of Words词袋模型进行描述，当然一般来说是用训练集的来构建词典，因为我们还没有测试集呢。虽然测试集是你拿来测试的，但是实际应用中谁知道测试的图片是啥，所以构建BoW词典我这里也只用训练集。 其实BoW的思想很简单，虽然很多人也问过我，但是只要理解了如何构建词典以及如何将图像映射到词典维上去就行了，面试中也经常问到我这个问题，不知道你们都怎么用生动形象的语言来描述这个问题？ 用BoW描述完图像之后，指的是将训练集以及测试集的图像都用BoW模型描述了，就可以用SVM训练分类模型进行分类了。 在这里除了用SVM的RBF核，还自己定义了一种核： histogram intersection kernel，直方图正交核。因为很多论文说这个核好，并且实验结果很显然。能从理论上证明一下么？通过自定义核也可以了解怎么使用自定义核来用SVM进行分类。(Image features used in a Dense Sift, by the Bag of Words bag model to describe the word, of course, the training set is generally used to build the dictionary, because we do not test set. Although the test set is used as the test you, but who knows the practical application of the test image is valid, so I am here to build BoW dictionary only the training set. In fact, BoW idea is very simple, although many people have asked me, but as long as you understand how to build a dictionary and how to image map to the dictionary D up on the line, and interviews are often asked me this question, do not know you all how to use vivid language to describe this problem? After complete description of the image with BoW, refers to the training set and test set of images are described with the BoW model, the training of SVM classification model can be classified. Apart from having to use the RBF kernel SVM, but also their own definition of a nuclear: histogram intersection kernel, histogram )

图像增强的matalab程序，里面有基于小波的，contourlet变换的，拉普拉斯塔等的增强，比较详细，有说明文件里面(Matalab image enhancement procedures, which have based on the wavelet, contourlet Transform, etc.拉普拉斯塔enhanced, more detailed, it has documentation)

说明：  卷积神经网络（Convolutional Neural Network）是一个专门针对图像识别问题设计的神经网络。它模仿人类识别图像的多层过程：瞳孔摄入像素；大脑皮层某些细胞初步处理，发现形状边缘、方向；抽象判定形状（如圆形、方形）；进一步抽象判定（如判断物体是气球）。(Convolutional neural network is a neural network specially designed for image recognition. It imitates the multi-layer process of human recognition image: pupil ingestion of pixels; some cells in the cerebral cortex preliminary processing to find shape edges and directions; Abstract judgment of shape (such as circles and squares); and further Abstract judgment (such as judging objects are balloons).)