divide

guided_filter滤波器。对于图像处理方面有用。(filter. It is useful for image processing.)

An simple illustration of champ markov

说明：  首先对指纹图像进行预处理，包括图像的分割，增强，二值化，细化。对细化后的图像进行特征点的提取，最后通过细节特征匹配完成指纹的识别。(Firstly, the fingerprint image is preprocessed, including image segmentation, enhancement, binarization and thinning. The refined image is extracted by feature points, and the fingerprint recognition is completed by minutiae feature matching.)

用于图像去噪的代码，有模型去噪、双树复小波去噪，希望有帮助。(Code for image denoising, a denoising model dual tree complex wavelet denoising, hope to have help。)

说明：  图像处理小工具箱，包括中值滤波，高斯滤波，均值滤波，canny边缘提取等小程序(Image processing toolbox, including median filter, gaussian filter, mean filter, canny edge extraction and other small procedures)

实现非均匀傅里叶变换代码，可用于石油地震勘探、航空航天、图像处理，电子电工方向。(Achieve non-uniform Fourier Transform code, can be used for seismic exploration, aerospace, image processing, electronics and electric direction.)

可以计算mtf，使用matlab输入图像即可实现计算(You can calculate MTF and use matlab to input images.)

图像的平滑函数，对指定区域的图像，并有门限值和魔板大小限制。(the smooth of a bmp image)

该算法首先通过字典学习得到含噪图像的冗余字典，然后对相似的图像块进行聚类构成块群，并通过迭代收缩和L1正则化约束，对同类的图像块在字典上进行稀疏表示，以达到降噪的目的。实验结果表明，在常规的图像处理上，本文提出的算法能较好的保留图像的结构信息，与K-SVD和BM3D等现有的流行算法相比，具有更高的峰值信噪比（PSNR）(It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the image patches are gathered according to their similarities.Meanwhile,the similar patches get sparse representation showed in dictionaries by iterative shrinkage and L1 regularization constraints and eventually the image is restored and noise is removed.The experimental results indicate that the proposed algorithm can well preserve the structure information of the common image with a higher Peak Signal to Noise Ratio(PNSR),compared with state-of-the-art algorithms,such as K-SVD and BM3D)

数字图像处理的入门介绍和一些函数、原理的使用，比较适合初学者使用(Introduction to digital image processing and some of the functions, the use of the principle, more suitable for beginners)