feikuai

说明：  小波变换是图像的多尺度、多分辨率分解，它可以聚焦到图像的任意细节，被称为数学上的显微镜。近年来，随着小波理论及其应用的发展，已将小波多分辨率分解用于像素级图像融合。把两个正交偏振的图片融合(Wavelet transform is the multi-scale and multi-resolution decomposition of an image. It can focus on any detail of the image and is called the mathematical microscope.In recent years, with the development of wavelet theory and its applications, wavelet multi-resolution decomposition has been applied to pixel-level image fusion)

图像阈值化分割,图像阈值化分割,图像阈值化分割(Image thresholding segmentation.Image thresholding segmentation.Image thresholding segmentation)

大量图片的处理代码,特别是图片的批量处理，非常有利于在处理图片时使用(A large number of image processing code, especially images of batch processing, image processing is very conducive to the use of)

该压缩包里包括了一幅图像的位平面解，即一幅灰度图像可以分成八个位平面。利用它可以转化到彩取色图像中去，很有用处的。(The bag includes a compressed image bit-plane solution, that is, a gray image can be divided into eight bit-plane. Use it can be transformed into the color check color images, and useful.)

fbp算法实现CT重建，包括不同投影个数、探测器个数和噪声对重建后图像的质量的影响。(FBP CT reconstruction algorithm, including the number of different projection, and the number of detector noise on the reconstructed image quality.)

基于K-means的优化聚类中心的图像分割算法，改进了FCM算法的缺点(Based on the optimization of K-means clustering center image segmentation algorithm to improve the shortcomings of the FCM algorithm )

在学习了数字信号处理、信号与系统、建模与仿真及其医学应用等课程的基础上， 学习一类典型的生物医学信号--脑电的测取、FFT 频谱分析、以及应用数字滤波方法提 取脑电的频带（8－13Hz）信号及其特性分析。(Epilepsy section of the brain wave extraction and analysis of characteristics of the course design report )

基因演算法, ~和吃飼料的演算法, e面的 ~吃到飼料會越來越快,(The genetic algorithm, the algorithm for eating feed, the e-plane algorithm for eating feed is getting faster and faster.)

有关粒子滤波及其改进算法的资料，对初学粒子滤波算法的人很有帮助(Information about particle filter and its improved algorithm, is of great help to beginners of particle filter algorithm )

说明：  利用BP神经网络进行图像分割。主要适用于RGB信息丰富的图像。以RGB为BP网络的三个输入，与对应的灰度图对网络进行训练。(The use of BP neural network image segmentation. RGB is mainly applied to information-rich images. BP network to RGB for the three inputs, with grayscale corresponds to the network training.)