block_global_motion

基于matlab指纹图像的分组法方向场求法(Based on matlab the fingerprint image dividing group method direction field is also given )

INSAR相位解缠绕程序，matlab编的(INSAR phase unwrapping procedures, matlab series)

) 使用分块的主成分分析方法(PCA)对人脸图像进行压缩编码。针对PCA方法计算量大的缺点,首先把问题转化成奇异值分解(SVD)问题,然后设计了特征空间的更新算法,通过递推,简化每一步计算的计算量,达到了实时编码的要求。 4) 在Windows平台下基于Video for Windows(VFW)接口开发了人脸视频图像编码和解码的实验系统,该系统实现了图像采集、图像显示、编码、解码等功能。() The use of sub-blocks of principal component analysis (PCA) on the human face image coding. PCA method for large defects, first of all the issues into a singular value decomposition (SVD) problem, and then design a feature space of the update algorithm, recursive, simplifying the calculation of the amount calculated at each step to achieve real-time encoding requirements. 4) In the Windows platform based on Video for Windows (VFW) interfaces, the human face image coding and decoding video experimental system, the system achieved image acquisition, image display, encoding, decoding functions.)

此程序利用openCV中人脸识别于模版匹配实现机器人的运动控制功能，其中机器人控制用了Aria的库和模拟器，使用者可根据控制需要替换这部分程序。 本程序的核心部分一直用于只能轮椅的人脸控制。(This process us face recognition in openCV and template matching to achieve robot motion control functions, which used the Aria library and robot simulator, user need replace this part of the control procedures to achieve their application.)

毕业论文参考，内含代码，基于小波变换的图像去噪算法(Image denoising based on wavelet transform, the graduation design code, matlab code)

利用稀疏表示进行图像去噪时，需要生成两种学习字典，该源码比较了生成的两种字典的优劣(Denoising sparse representation, it is necessary to generate two learning dictionary, which compares the generated source code of the merits of two dictionary)

全套的DCT域数字水印源代码matlab(A full set of digital watermarking of DCT-domain source code matlab)

用扩散滤波实现图像增强，包括高斯滤波预处理，梯度计算，结构张量计算，扩散张量计算，数值离散以及增强效果评估代码(Diffusion-image enhencement)

同态滤波器 作用：消除不均匀照度的影响, 增强图象细节。(Filter function with the state: to eliminate the impact of uneven illumination, enhanced image detail.)

图像分割--用matlab实现图像的自动多阈值分割 (Image segmentation- Image by matlab automatic multi-threshold segmentation)