tsp_hopfield

自动种子区域生长代码，用MATLAB运行，不必选择种子点 可以自动选择阈值 实现图像分割！(The automatic seed region growing code, run, do not have to select seed point can automatically select the threshold image segmentation using MATLAB)

说明：  给定两张图片，利用ssim来计算两张图片他们之间的ssim相似度(compute ssim between two images)

数字图像处理图像复原算法源代码（维纳滤波，最小二乘方法，L-R算法）(Digital image processing, image restoration algorithm source code (Wiener filtering, least squares method, the LR algorithm))

本文档主要讲解了基于图论着色的动态频谱分配研究，可以让大家快速的学习认知无线电中的频谱分配(This document is mainly on the dynamic spectrum allocation based on graph coloring theory research, so that we can quickly learn the spectrum allocation in cognitive radio)

利用Hough变换，可以检测图像中的多条线段，效果很好(using hough transform for line detection)

用于信号特征提取、信号消噪，MinkowskiMethod算法 ,未来线路预测,分析误差。( For feature extraction, signal de-noising, MinkowskiMethod algorithm, Future line prediction, error analysis.)

数字图像处理的入门介绍和一些函数、原理的使用，比较适合初学者使用(Introduction to digital image processing and some of the functions, the use of the principle, more suitable for beginners)

实现数字图像小波阈值去噪，显示软硬阈值处理过后的信噪比(Implementing Wavelet Threshold Denoising of Digital Image)

说明：  （1）图像基本操作：不同格式（大于3种）图像的读入与存盘、文字叠加、不同彩色空间的转换、图像的DCT及FFT变换等； （2）图像增强：包括直方图拉升（线性和非线性）、直方图均衡、平滑与锐化（采用不同的滤镜），美颜（加分项）； （3）图像恢复：几何操作（如旋转、缩放、投影校正等）、模糊恢复（如运动模糊消除等，加分项）； （4）图像合成（加分项）：实现换头、换背景、图像拼接等功能。((1) Basic operation of image: reading and saving of images in different formats (more than 3 kinds), text superposition, conversion of different color spaces, DCT and FFT transformation of images, etc; (2) Image enhancement: including histogram lifting (linear and non-linear), histogram equalization, smoothing and sharpening (using different filters), beauty (bonus item); (3) Image restoration: geometric operations (such as rotation, scaling, projection correction, etc.), blur restoration (such as motion blur elimination, etc., plus points); (4) Image synthesis (Bonus): realize the functions of head changing, background changing, image splicing, etc.)

使用Gabor小波对图像进行特征提取，代码可以直接使用(Using the Gabor wavelet feature extraction, the code can be used directly)