fenjiechonggou

A fast customizable function for locating and measuring the,

ZIGZAG程序，实现对图像矩阵ZIGZAG顺序读取。通常作为函数调用。还有就是霍夫曼编码的程序，得到图像霍夫曼的编码(ZIGZAG procedures ZIGZAG image matrix to achieve the order read. Usually as a function call. There is the Huffman code procedure, the image encoding Hoffman)

说明：  IFC文件格式读取和写出源码，目前该源码是1.0版本(IFC file format reads and writes the source code, which is currently version 1.0)

近似熵算法对脑电信号进行特征提取的一些材料(Some materials approximate entropy algorithm for EEG feature extraction)

在matlab环境中用快速傅里叶变换实现多目标追踪，计算的非常快(Matlab environment using the fast Fourier transform to achieve multi-target tracking, very fast calculation)

汽车车牌数字识别（上个学期的数字图像处理的课程设计），能运行(Automobile license plate number identification (the last semester of digital image processing course design), can run)

一种基于MC算法的医学图像三维重建，或许有用(MC algorithm based on three-dimensional reconstruction of medical images, perhaps useful)

estimate shape of a noisy image from the shading information

说明：  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)

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.)