codes3_GUI

经典数字图像处理算法仿真，包括图像的傅里叶滤波及压缩，图像的DCT高通、低通滤波，图像直方图均衡化，图像平滑与锐化，图像的模糊化，哈夫曼编码等，以及GUI图形化界面。(Classic digital image processing algorithm simulation, including Fourier filtering and image compression, image DCT high-pass, low-pass filtering, image histogram equalization, image smoothing and sharpening, blurring the image, Huffman coding, as well as GUI graphical interface.)

说明：  根据：基于不变矩特征和神经网络的图像模式模糊分类 论文 在matlab上做的实验，有7个不变矩生成和神经网络分类的代码，还要论文原文(According to: Based on the characteristics of moment invariants and neural network image mode fuzzy classification papers in matlab to do the experiment, there are seven moment invariants and neural network classifier to generate the code, but also the original papers)

基于sift的图像拼接算法，使用matlab实现(Sift-based image mosaic algorithm implementation using matlab)

混合高斯前景提取。数学建模时编的，测试视频就在包内，可以作为学习交流用，环境2014a的matlab，后有添加形态处理都在注释里。一起学习。有matlab编的vibe程序欢迎交流(Hybrid Gauss foreground extraction. Mathematical modeling of the series, the test video is in the package, can be used as a learning exchange, the environment 2014a MATLAB)

matlab函数，将多维矩阵的极值找出并定位，图像处理经常用到，很简单很好用(matlab function, multi-dimensional matrix to identify and locate the extreme, often used in image processing, it is very simple to use)

用于求解凸优化问题，恢复低秩密度矩阵问题(this matlab Algorithm can be used for the convey optimal problen, and also for the low-rank density matrix reconstruction)

说明：  slic超像素分割，可以实现图像的超像素分割(SLIC super pixel segmentation)

FDK重建算法 希望对其他人能有帮助 用C和cuda 实现的(fdk reconstrcution algorithm using cuda and c source code hope to help others it may be usefull. it is implented by c and cuda)

对李纯明的DRLSE进行了改进 利用各向异性扩散提高了分割弱边缘的能力 改进的高斯滤波代替惩罚项 加快了演化速度 节省了时间(The DRLSE to LiChunMing improved using anisotropic diffusion improve the segmentation of improvement of the ability weak edge gaussian filtering instead of penalty term accelerated evolution speed save time)

某个平面内的一系列点的密度分布，通过求出x和y方向的点的概率，最后用矩形框画出密度大的区域。4000个数据，详解，效果不错，直接能运行。(The density distribution of a series of points in the plane, determined by the probability of the point x and y directions, the final draw-density region with a large rectangular box. 4000 data, explain, good results can be directly run.)