第 27 章 基于区域生长的肝影像分割系统

一种图像对比度增强算法，包含demo，和图像性能测试(An image contrast enhancement algorithms, including demo)

对两帧图像进行ICM调试.包含内容：1估计姿态和摄像机内参数；2两幅图做四次金字塔；3利用输入特征点采用ransac算法估计姿态R, T。4sift特征匹配；5摄像机标定。(ICM images on two debugging. Contains: 1 Estimated posture and intrinsic parameters 2 two plans to do four pyramids 3 using the input feature points using ransac algorithm estimates gesture R, T. 4sift feature matching 5 camera calibration.)

光学组件的matlab工具包，利用它，你可以仿真spot，几何像差，如慧差，球差，还有mtf仿真等(Optical components matlab toolkit, use it, you can simulation spot, geometric aberration, such as the Hui poor, spherical aberration, as well as simulation mtf)

说明：  相位恢复算法,gs算法，适用于双强度测量的相位恢复问题(a phase retrieval algorithmn-gs using MATLAB)

基于最优小波包的特征提取 大家可以参考 基于最优小波包的特征提取 大家可以参考基于最优小波包的特征提取 大家可以参考(Based on best wavelet packet feature extraction we can refer to based on best wavelet packet feature extraction we can we can refer to reference based on best wavelet packet feature extraction)

说明：  利用Hessian矩阵的滤波函数Frangi，再血管图像处理上有很好的应用(Using the filter function Frangi of Hessian matrix, there is a good application in revascular image processing.)

首先利用形态学开运算将图像中小于结构元素的亮点去掉，利用源图像与处理后的图像作差，对差图像进行阈值分割，得到二值图像，将二值图像中的一些干扰区域去掉，提取二值图像中的圆形区域，并在源图像上对小目标进行标记，实现对圆形亮目标的检测(Remove the area in the image smaller than structural element by morphologic open operation，receive image A，original image subtract image A，threshold segmentation for difference image，receive binary image，remove the interference region in the binary image，then extract circular area，and sign the target in the original image. Realize the circular bright target detection)

some fast feature extraction algorithms are addressed for joint retrieval of images compressed in JPEG and JPEG2000 formats. In order to avoid full decoding, three fast algorithms that convert block-based discrete cosine transform (BDCT) into wavelet transform are developed, so that wavelet-based features can be extracted from JPEG images as in JPEG2000 images.

基于ADMM的TV正则化最小化稀疏重建算法(TV Minimization Sparse Reconstruction Algorithms Based on ADMM)

说明：  ORL人脸图像库，共40人，每人10幅图像，其中每人的前5幅作为训练样本，后5幅作为测试分类样本，统计正确分类率。分类准则为最近邻规则。 真实的图像尺寸为112x92，列向量堆积对应人脸库矩阵的每一列。 (ORL face image database, a total of 40 per 10 images, each of which the first five as training samples, after the 5 categories as a test sample, correct classification rate statistics. Classification criteria for the nearest neighbor rule. The real image size is 112x92, the corresponding column vector face database matrix accumulation of each column.)