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本书主要讨论了图像的各类矩函数（几何矩、复数矩、Legendre矩、Zernike矩、小波矩等）的定义、性质和快速算法，以及它们的不变量函数。并就它在图像处理和识别，计算机视觉以及其它方面的应用作了必要的介绍。 (This book discusses the various types of image moment function (geometric moments, complex moments, Legendre moments, Zernike moments, wavelet moment, etc.) of the definition, nature and fast algorithm, and their non-variable function. On it in the image processing and recognition, computer vision, and other aspects of the application made the necessary introduction.)

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.)

代码使用全相位双正交变换（APBT）稀疏表示图像，主函数为test.(The code uses the all phase biorthogonal transform (APBT) sparse representation of the image, the main function for the test.)

转换八位256色位图源码，例程程序置入汇编代码，通过图像字节集数据的计算转换为八位256色位图。(Conversion of eight 256-color bitmap source , routine program into assembly code to calculate the conversion by the image data into eight byte set 256-color bitmap .)

itk 阈值分割 大津法分割 医学图像分割(itk Otsu threshold segmentation method segmentation medical image segmentation)

基于频率锁定环路和相位锁定环路级联，高斯噪声下的高动态实现载波跟踪(Based on frequency-locked loop and a phase locked loop cascade, the Gaussian noise high dynamic carrier tracking)

Matlab下，读取raw文件，实现多波段图像融合，高光谱与高分辨率图像融合，包括直接融合，傅里叶变换后融合，小波变换后融合及HIS变换后融合。(On Matlab,how to read and show raw files, achieve more band mergering,spectrum image and high resolution image fusiing,including direct fusion,Fourier transform fusion, wavelet transform fusion and HIS transformation fusion )

视网膜血管分割的matlab版本算法，该算法分割较为细腻(Retinal blood vessel segmentation)

对特征值进行非极大值抑制的角点检测，并且选用了合适的阈值加强检测效果(corner detection by non-maxima suppression of Eigenvalues and selected the appropriate threshold to enhance detection)

说明：  一个用matlab编写的源程序，可以实现基于颜色直方图的图像检索(A source code written with matlab, you can achieve the color histogram-based Image Retrieval)