lizilvbo

Zernike矩，分为一个主函数和六个子函数，主要步骤有注释，方便理解，有图，方便使用。主程序前段更改了判断输入参数个数的代码(Zernike moments, divided into a main function and six subroutines, major steps have comments, easy to understand, map, easy to use. The main front-end change the code determine the number of input parameters)

FCM源代码，专门用于图像分割的，速度很快(FCM source code, specifically for image segmentation, very fast)

基于灰度直方图的otsu（大津法）改进算法实现图片前景背景分离（matlab代码，实验报告）(Improved algorithm based on gray-scale histogram the otsu (Otsu method) background picture prospects separation (Matlab code, lab report))

对图像稀疏编码和字典学习有个大致的了解，以及当前的研究现状(Sparse Coding and Dictionary)

使用MATLAB生成二维voronoi图的代码，可以用作后续二维voronoi的多晶模型建立(The code of two-dimensional Voronoi diagram generated by MATLAB can be used to build the polycrystalline model of two-dimensional voronoi.)

说明：  BMED二维经验模态分解，用于处理二维信号(Two dimensional empirical mode decomposition)

离散傅里叶变换、离散余弦变化、离散小波变换(Discrete Fourier transform, discrete cosine transform and discrete wavelet transform)

此程序计算图像的七个不变矩，提取出图像的形状特征，可用于图像检索。(This procedure of calculating the image of seven invariant moments, the shape of extracted image features, can be used for image retrieval.)

oif波段选择算法，可以用于对高光谱图像进行波段选择(oif band selection code of matlab)

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.)