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最小二乘匹配，图像匹配算法，需要初始匹配坐标，可以达到亚像素精度(least squares matching, image matching algorithm, the initial need to match coordinates, can reach sub-pixel accuracy)

一些常用的高光谱解混方法的matlab代码(Hyperspectral unmixing method matlab code)

说明：  使用matlab编写的源程序 高斯噪声产生的源代码(prepared by the use of Matlab source Gaussian noise source)

将图片进行8*8块的dct变换，以及8*8块的反变化恢复原图像(use 8*8 block dct to chang image, and use 8*8 block idct to renew image.)

matlab实现的小波降噪声图像处理算法，效果十分好，自己做了调试。(The wavelet reduced noise image processing algorithm realized by Matlab is very effective and has been debugged.)

图像检测的算法，Faster R-CNN算法，先对整张图像进行卷积计算，然后通过感兴趣区域池化层(RoI Pooling Layer)将选择性搜索算法推荐出来的候选区域和卷积网络计算出的特征映射图进行融合，得到候选区域对应的特征矢量，这种共享卷积计算的操作极大地减少了卷积计算的次数。而且这些特征矢量的维度统一，方便后续的分类工作。通过感兴趣区域池化层处理卷积特征，并将得到的特征送往两个并行计算任务进行训练，分类和定位回归。通过这些方法和改进的框架，Fast R-CNN 用更短的训练和测试时长，取得了比 R-CNN 更好的效果(Faster R-CNN algorithm first convolutes the whole image, then fuses the candidate regions recommended by the selective search algorithm and the feature mapping maps calculated by the convolution network through the RoI Pooling Layer to get the corresponding feature vectors of the candidate regions, which greatly reduces the number of convolution calculations. Moreover, the dimension of these feature vectors is unified, which facilitates the subsequent classification work. The convolution feature is processed by the pooling layer of the region of interest, and the obtained feature is sent to two parallel computing tasks for training, classification and positioning regression. Through these methods and improved framework, Fast R-CNN uses shorter training and testing time and achieves better results than R-CNN.)

冈萨雷斯数字图像处理所有例子源码全解 (failed to translate)

利用Matlab的图形用户界面（GUI）编程实现1.信号产生,信号基本运算,傅立叶变换 2.图像文件的读取和显示,图像增强,边缘检测,图像的数学变换(Using Matlab' s graphical user interface (GUI) programming 1. Signal generation, signal basic operations, Fourier transform 2. Read and display image files, image enhancement, edge detection, image of the mathematical transformation)

此算法为基于k-means聚类的非局部均值快速去噪算法，方法便捷有效，可保持边缘信息(this is a fast edge-preserving denoising method based on non-local means method with k-means clustering)

完整的图像加密算法以及对此算法加密结果的性能分析：像素之间相关性，图像的信息熵，以及NPCR,UACI(completely figure encryption scheme and corespond result analysis)