资源列表
多光谱图像读取
- 使用MATLAB读取多光谱类图像，对真彩色图像进行去相关增强处理。
数字水印图像的嵌入和提取源代码
- 有载体图像和水印图像，基于DCT变换将水印图像嵌入载体图像中，肉眼不可感知，然后经过DCT逆变换提取水印图像，至此实验完成。
偏最小二乘PLS和一些光谱预处理的matlab程序
- 可以对光谱数据进行预处理，除了偏最小二乘法之外，也有一些其他方法(Besides the partial least square method, there are also some other methods)
BlindWatermark
- 基于PYthon的盲水印实现，目前相对成熟，仔细校对过代码，对暴力破坏的图片依旧有良好的水印还原。该技术源码需要一定的PYthon基础才能使用，(The implementation of blind watermark based on Python is relatively mature at present. After carefully proofreading the code, there is still a good watermark restoration for the
InSAR MATLAB
- 荷兰Delft大学开发的insar（干涉合成孔径雷达）图像处理部分源代码，用matlab编写的。
CCMD_OCR
- OCR图像文字识别源码，使用OCR图像识别控件，支持bmp,jpg,tif等多种图形格式的文字识别。(OCR image text recognition source code, use OCR image recognition control, support bmp, jpg, tif and other graphic format text recognition.)
遥感图像配准系统
- 本程序主要对遥感图像实现三种处理：几何校正、图像增强和图像配准。这三种处理都可以独立实现，然而对于原始的遥感图像将这三种处理依次进行效果更佳。(This program mainly deals with three kinds of remote sensing image processing: geometric correction, image enhancement and image registration. These three kinds of processing can
Image Noise Level Estimation by Principal Component Analysis
- 论文Matlab实现：S. Pyatykh, J. Hesser, and L. Zheng, "Image Noise Level Estimation by Principal Component Analysis", IEEE Transactions on Image Processing, Volume: 22, Issue: 2, Pages: 687 - 699, February 2013.
干涉条纹
- 使用matlab识别干涉条纹。通过形态学处理，识别干涉条纹数，并计算出条纹间距。内包含交互界面。(The interference fringes are identified by matlab. Through morphological processing, the number of interference fringes is identified and the fringe spacing is calculated. It contains an interactive in
傅里叶变换
- 傅里叶变换，时域和频域图同时，简介方便，可以自行修改采样频率(Fourier transform, time domain and frequency domain graph simultaneously)
基本数字水印和DCT数字水印
- 掌握基本数字水印和DCT数字水印的实现和检测方法；检验DCT数字水印，抵抗高斯噪声攻击、椒盐噪声攻击、剪切攻击和旋转攻击的能力。(Grasp the implementation and detection methods of basic digital watermarking and DCT digital watermarking, and test the ability of DCT digital watermarking to resist Gauss noise attack,
机器视觉的零件缺陷和瑕疵检测
- 机器视觉的零件缺陷，瑕疵检测，特征匹配，效率高速度快(Machine vision parts defects, defect detection, feature matching, high efficiency and speed)