vibe_tom

若干次压缩后图像信噪比的变化情况，有子程序实现 (Several compressed image signal to noise ratio of the changes have Subroutine realize)

说明：  应用三维重构原理对二维平面图形重建成三维图像。(Application of the principle of three-dimensional reconstruction of two-dimensional graphical reconstruction into three-dimensional image.)

基于感兴趣区域的图像检索。matlab的，希望对大家有所帮助。(Region of interest based image retrieval. matlab, and want to help everyone.)

马尔科夫随机场 EM算法 做图像变化检测 请多指教(MRF EM image change detection algorithms do please advise)

说明：  基于BP神经网络的鼠标手势识别算法与实验程序GestureStudy(BP neural network based on the mouse gesture recognition algorithm and experimental procedures GestureStudy)

虹膜识别中的特征提取算法：2D-Gabor滤波器算法，将归一化的虹膜图像由此滤波器滤波，可以得到二进制的特征编码。附图片。(Iris recognition in the feature extraction algorithm: 2D-Gabor filter algorithm, the normalized iris image resulting filter can be obtained characteristics of the binary encoding. Attached picture.)

说明：  将已知的灰度图像逆时针旋转60度，矩阵运算，图像旋转(Rotate the known grayscale image 60 degrees counterclockwise, matrix operation, image rotation)

对采样得到的180幅断层图像进行重建，并针对其中的一幅图像进行处理，并且统计图像中颗粒的大小和数目！(Tomographic images of 180 samples obtained were rebuilt, and for which an image processing and image size and number of particles statistics!)

一种基于半监督的svm的图像分类方法。该方法通过聚类核的方法利用无标记样本局部正则化训练核的表达式。这种方法通过图像直接学习一个自适应的核。该程序仿真的是文章：Semi-supervised Remote Sensing Image Classification with Cluster Kernels。大家可以参考下。(A semi-supervised SVM is presented for the classification of remote sensing images. The method exploits the wealth of unlabeled samples for regularizing the training kernel representation locally by means of cluster kernels. The method learns a suitable kernel directly from the image, and thus avoids assuming a priori signal relations by using a predefined kernel structure. Good results are obtained in image classification examples when few labeled samples are available. The method scales almost linearly with the number of unlabeled samples and provides out-of-sample predictionsds)

傅里叶变换：采用VC++编写，实现二维图像的傅里叶变换(Fourier Transform: The VC++ prepared to achieve the two-dimensional Fourier transform of the image)