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本书详细介绍了医学图像注册方面的知识，包括配准的原理、刚性配准、非刚性配准，对于医学图像处理方面的研究具有很重要的参考价值。(The book details the registration of medical image information, including the principle of registration, rigid registration, non-rigid registration for medical image processing research has important reference value.)

说明：  使用sift进行的图像拼接，matlab语言实现(Image mosaic using sift)

三维人脸数据库FRGC V1. 0,2.0包括图像的深度数据和纹理，格式分别保存为：abs和ppm 读取abs数据中的深度z轴数据，保存为480*640的矩阵，进而进行数据处理研究。并且贴ppm纹理，便于观察。 (Three-dimensional face database FRGC V1. 0,2.0 depth data including images and textures, formats were saved as: abs abs data and ppm reads depth z-axis data, save it as a 480* 640 matrix, and then studied for data processing . And paste ppm texture, easy to observe.)

通过帧差法来提取背景的程序，效果不错通过帧差法来提取背景的程序，效果不错‘(通过帧差法来提取背景的程序，效果不错通过帧差法来提取背景的程序，效果不错)

基于边缘检测和区域生长的自然彩色图像分割源码(Based on edge detection and region growing source of natural color image segmentation)

说明：  基于脉冲耦合神经网络的图像分割，脉冲耦合神经网络是近年研究的热点。(Based on Pulse Coupled Neural Network for Image Segmentation, pulse coupled neural network is the research hotspot in recent years.)

基于openCV的gabor函数,一位牛人编写的。希望对大家有用(gabor function based on openCV)

idl进行波段运算的小程序band_math(idl procedures for small-band operation)

提出了一种大容量的可逆信息隐藏算法的详细实现方案。利用图像直方图中的多个零点或者最小点, 通 过修改图像像素的灰度值来隐藏信息, 并通过统计分析给出常用的信息隐藏的模型和算法。(Presents a large reversible capacity detailed information hiding algorithm implementations. Using the image histogram, or the minimum number of zero points, by modifying the image pixel gray value to hide the information, and is given by commonly used statistical analysis model and algorithm for information hiding.)

提出了一种结合USFFT Curvelet 变换的各向异性扩散图像去噪模型。它有机结合了Curvelet 变换和各向 异性扩散（P-M扩散）两者的优点。通过P-范数方法选择合适的梯度阈值K，P-M扩散过程通过处理经过Curvelet 变换得到的图像的不同尺度的Curvelet 系数矩阵，实现了建立在对图像多尺度分析的基础上的新P-M扩散模型。 实验表明，新模型的处理结果能有效避免传统P-M 扩散出现的阶梯效应，同时更好地保留图像的纹理和细节。 关键词：图像去噪算法；各向异性扩散；Curvelet 变换；P-M 扩散(Abstract: An image de-noising model by integrating anisotropic diffusion with USFFT Curvelet transform was proposed, which combined the strongpoint of Curvelet transform with anisotropic diffusion (P-M diffusion). By choosing appropriate gradient threshold K through p-norms and carrying out the P-M diffusion process depend on the different scale matrixes of Curvelet coefficient of the image from Curvelet transform iterations, as a result, the improved model made it possible to carry out the new P-M diffusion de-noising process based on multi-scale analysis of the image. The experiment results have demonstrated that the model can avert the stair-casing effect in the traditional P-M diffusion effectively and keep the textures and details of images better.)