激光雷达数据处理

晨宇思远博客的代码------文件中代码实现小波图像融合，对低频和高频系数采用不同准则，有详细说明文件中代码实现小波图像融合，对低频和高频系数采用不同准则，有详细说明( morning yu siyuan blog code----------- file code implements wavelet image fusion, the low frequency and high frequency coefficient using different criteria, there are detailed description file code implements wavelet image fusion, the low frequency and high frequency coefficient using different criteria, there are elaborate)

radarsat1 的成像程序，包括源码，是个很好用那个的算法(radarsat1 imaging procedures, including source code, is a good use of that algorithm)

说明：  快速图像修复的各种算法 各种算法详尽的表述及其相互比较(Fast image restoration algorithms detailed presentation of the various algorithms are compared)

文件包含了基于米散射的球形代码...可用于计算球形粒子的基本光学参数..如消光效率，吸收效率..散射光强.单次散射反照率以及不对称因子等等....(File contains the code based on Mie scattering spherical ... spherical particles can be used to calculate the basic optical parameters .. as extinction efficiency, absorption efficiency .. scattering intensity single scattering albedo and asymmetry factor and so on ....)

该代码采用IDL语言实现了从光谱库读取高光谱曲线，并且去除其包络。这是高光谱图像处理时一个重要的预处理技术。(The code using IDL language library to read from the spectrum of high spectral curve, and the removal of the envelope. It is time hyperspectral image processing is an important pre-processing techniques.)

运用Perona-Malik各向异性扩散模型对3d图像进行平滑去噪。此方法可以有效的抑制高斯噪声，并保护图像的边缘特征。(The use of Perona-Malik anisotropic diffusion model for smooth 3d image denoising. This method can effectively suppress Gaussian noise and to protect the image of the edge feature.)

VMD分解阈值去噪，进行极优模态分量的选择(VMD decomposition threshold denoising, selection of very excellent modal components.)

基于MAP(最大似然概率）的图像超分辨重建(map-based images super-resolution construction)

本代码主要给出了激光粒度仪颗粒散射光强分布以及4种粒度反演算法，以及4种算法之间的比较。四种反演算法为：TSVD、Chaine、Tikhonov和l1正则化。(The code gives the Zetasizer particle scattering intensity distribution, and four kinds of particle inversion algorithm, as well as a comparison between the four algorithms. Four kinds of inversion algorithm is: TSVD, Chaine, Tikhonov and l1 regularization.)

说明：  取一个最优阈值把原图像分为前景色与背景色，两部分的类间方差越大，说明两部分差别越大，便能有效的分割图像。(Image threshold segmentation)