基于PCA-LDA光谱数据的降维处理

说明：  灰度图像的边缘检测，包含多种算子：sobel,prewitt,gaosi算子等，包括原理和各算子的区别(Edge detection of gray image includes many operators: Sobel, Prewitt, Gaosi, etc)

自己编写的字幕提取代码，matlab简单易用(Caption extraction)

说明：  利用BP算法进行SAR成像，BP算法是一种对时域回波数据进行成像的算法(BP algorithm was used for SAR imaging)

基于NSCT变换的自适应去噪，里面包含仿真图(image denoising)

天津工业大学课程设计，内容包含vs2010对图像的灰度化，二值化，边缘检测。包含单纯c语言编写的对图像的灰度化，二值化，边缘检测的一个.C文件，可以直接用vc6.0运行，也可以直接在DSP上运行，还包含一份详细的设计报告。(Tianjin Polytechnic University curriculum design, content includes vs2010 grayscale image binarization, edge detection. Contains pure c language for image graying, binarization, edge detection is one. C file that can be run with vc6.0 can also be run directly on a DSP, also contains a detailed design report.)

图像的自动拼接和缝补，采用sift算法作为匹配，是学习全景图像拼接的基础，大家可以下载下来看看(Automatic image stitching and sewing, using sift algorithm as a match, is the basis for learning panoramic image mosaic, you can download to see)

Keren 配准的MATLAB源程序，可以进行图像配准及超分辨率运算(Keren registration of the MATLAB source code)

基于主成分分析与灰度（颜色）、纹理（灰度共生矩阵）的图像分类matlab程序（附示例图像）。(Image classification matlab program based on principal component analysis and gray (color), texture (GLCM) (with sample images).)

matlab电子稳像块匹配算法程序代码 图片路径请自行更改(Electronic Image Stabilization matlab code image block matching algorithm to change the path at your own)

说明：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)