Harris

本程序集合了互信息配准，PV差值，powell算法，基于小波变换的图像融合的一整套算法。只需要在GUI界面输入两幅图像，即可自动完成图像的配准融合。程序包含Matlab源代码。用Matlab打开imagefusion.m，即会弹出gui界面。融合前要输入参考和浮动图像。图像要求像素的 长＊宽 一样。否则会报错。程序只能处理灰度图像，彩色图像也会转化成灰度图像处理。程序代码已经有详细的注释，方便读者理解。(The procedures set of mutual information, PV difference, powell algorithm, based on wavelet transform image fusion set of algorithms. Only need to enter the two images in the GUI interface, you can automatically complete the image registration fusion. Program contains Matlab source code. Using Matlab open imagefusion.m, gui interface will pop up. Fusion before the input reference and floating images. Image requires the same pixel length* width. Otherwise incorrect. Can only handle grayscale images, color images into gray image processing also. Program code has detailed notes, to facilitate understanding.)

说明：  通过Logistic映射与Chen超混沌系统产生随机序列的DNA分块编解码图像加密技术(Image encryption technology of DNA block encoding and decoding by using logistic map and Chen hyperchaos system to generate random sequences)

Pixel design for H-noise cal; imageJ platform ; test done

提取糖尿病视网膜病变眼底图像上硬性渗出。将彩色图像转为灰度图，对灰度图进行形态学处理、去背景、阈值分割，最终将原图上的硬性渗出区域用绿色标记出来。(this word is to extrac the hard exudates on diabetic retinopathy fundus image. The color image to grayscale on grayscale morphological processing to the background, threshold segmentation, ultimately on the original hard exudates area marked in green.)

基于马尔可夫随机场(MRF)、条件迭代算法ICM的图像分割源码(The MRF, the ICM-based image segmentation source code to source image segmentation based on the MRF ICM)

实现了geodesic active contour图像分割算法，用到AOS scheme and level set method(Realize the geodesic active contour image segmentation algorithm, using AOS scheme and level set method)

当前流行的机器学习算法之一：boosting的变体——Gentleboost(The current popular one of machine learning algorithms: boosting variants- Gentleboost)

裁剪以RGB565格式保存的BMP文件，涉及位图掩码内容(imagecut of the BMP picture which saved with RGB565 format and mask)

说明：  在MFC中显示各种格式的图片，jpg.png(Display pictures in various formats in MFC, jpg.png)

使用python语言实现多张图像的拼接，并且处理拼接之后的裂缝和黑边。(Use python language to achieve splicing of multiple images, and deal with cracks and black edges after splicing.)