PCA-based-image-fusion

matlab读入IGS文件，通过把IGS文件读入，实现三维数据点的显示，有利于matlab编辑(read into matlab IGS file read by IGS file to achieve a three-dimensional data points show favor matlab edit)

Laplasian图像边缘提取，亲测有效，欢迎下载使用。(Edge extraction of Laplasian image)

通过Python画出两种比较容易的小花。(We draw two simple and ugly flowers by Python.)

基于谱间预测的高光谱图像压缩。单向预测与双向预测，以及参考波段的最优选取(The prediction based on spectral hyperspectral image compression. One-way bi-directional prediction and prediction, as well as reference to select the optimal band)

利用Kalman Filter进行机动目标跟踪的例子,附有详细的说明文档,(Examples of using Kalman Filter for maneuvering target tracking, a detailed documentation,)

BMP24位位图量化成256色BMP图，本程序彩八叉树颜色量化。(BMP24-bit quantization into a 256-color bitmap BMP map, this program color octree color quantization.)

通过矩阵变换，实现二维图像在给定角度下的旋转。(By matrix transformation, achieve the rotationa of a two-dimensional image in a given angle .)

最大类间方差法是由日本学者大津(Nobuyuki Otsu)于1979年提出的,是一种自适应的阈值确定的方法,又叫大津法,简称OTSU。它是按图像的灰度特性,将图像分成背景和目标2部分。背景和目标之间的类间方差越大,说明构成图像的2部分的差别越大,当部分目标错分为背景或部分背景错分为目标都会导致2部分差别变小。(The largest between-class variance method was proposed by the Japanese scholar Nobuyuki Otsu in 1979. It is an adaptive threshold determination method, also known as the Otsu method, or OTSU for short. It is based on the grayscale characteristics of the image and divides the image into two parts: the background and the target. The larger the variance between the background and the target, the greater the difference between the two parts that make up the image. When the part of the target is wrongly divided into backgrounds or part of the background is mis-divided into goals, the difference between the two parts will be smaller.)

PCA IMAGE FUSION ,A GOOD MATLAB FILES

一种属性离散化的方法，对粗糙集适用(An attribute discretization method, the rough set for)