IMM_ct

图像检索中经典的SIFT方法matlab实现，由NTU的大牛撰写，做了些批注。(SIFT for image retrieval，feature extraction and matching)

SRCNN Superresolution imteplated by tensorflow SRCNN tensorflow 实现(SRCNN Superresolution imteplated by tensorflow)

1.本程序功能包含显示直方图，OTSU的单值分割，OTSU的二值分割,OTSU的三值分割 2.在OTSU的分割时，通常情况下我们是通过类间方差得到一个分割阈值，但是有时候我们需要得到各灰度级别的目标，那么采取多值分割是 很必要的，通过改进得到OTSU的多值分割方法 3.本程序另外还有显示直方图，计算程序运行时间，处理结果以新的窗口显示等细节，这部分适合MFC初学者。(1. This procedure shows the histogram feature, OTSU single segmentation, OTSU binary segmentation, OTSU three segmentation 2. OTSU segmentation, it is usually the case we are through the between-cluster variance by a partition threshold , but sometimes we need to be the gray level of the target, then the multi-segmentation is necessary, through improved access to multi-OTSU segmentation methods 3. This procedure in addition to show the histogram to calculate run time, treatment the results of a new window display the details of this part of MFC for beginners.)

动目标检测，包括动目标检测理论，动目标检测器，目标检测公式(Moving target detection, including moving target detection theory, moving object detection, object detection formula)

对于离焦图像进行自动对焦的图像判定，通过对一些列的图像，从离焦到对焦再到离焦进行图像分析从而获得对焦图像的图片。(For the defocus image autofocus image determination, through a series of images into focus and then from defocus defocused image analysis to obtain a focused image of the picture.)

下面给出了48项泽尼克多项式，外加一项常数项。需要注意的是，读者并不需要严格按照下文所示的顺序排列这些泽尼克项，实际上在不同的应用和机构会采用不同的排列顺序。 表中的#0项是个常数或者说是平移项（piston term），这一项的系数也代表了平均光程差；而#1和#2项分别是x和y方向的倾斜项（tilt terms），#3代表了聚焦，因此，#1到#3项代表了波前的高斯或者近轴特性；#4和#5项代表了像散和离焦，#6和#7项代表彗差和倾斜，而#8项代表了3级像差和离焦，也就是说#4到#8项为3级相差项；同样地，#9到#15项代表了5级像差，而#16到#24项代表了7级像差，#25到#35项代表了9级像差，#36到#48项代表了11级像差。(Here are 48 Zernike polynomials, plus a constant term. It is important to note that the reader does not need to strictly arrange the Zernike entries in the order shown below, but in fact different orders of arrangement are applied to different applications and institutions. Table #0 is a constant or a shift (piston term), a coefficient of this term also represents the average optical path difference; while #1 and #2 are inclined X and Y direction (tilt terms), #3 represents the focus, therefore, #1 to #3 on behalf of the wavefront. Gauss or paraxial properties; #4 and #5 represent the astigmatism and defocus, #6 and #7 represent coma and tilt, and #8 represents the 3 order aberration and defocus, that is to say #4 to #8 is 3 level difference; similarly, #9 to #15 on behalf of the 5 order aberration #16 and #24, to represent the 7 level #25 to #35 aberration, on behalf of the 9 #36 to #48 aberration, on behalf of the 11 order aberration.)

基于分水岭自动选取种子的区域生长来进行彩色图像分割(Automatically selected based on the watershed to the seed region growing for color image segmentation)

本代码实现了基于卡方分布(nakagami 分布)的恒虚警检测(CFAR)，通过在查找表的形式，实现参数估计和阈值估计，完成对目标的检测。(The code based on the chi-square distribution (nakagami distribution) of the CFAR (CFAR), through the form of a lookup table to achieve the threshold parameter estimates and estimates to complete the target detection.)

说明：  基于opencv的支持向量基（SVM）的代码，利用SVM解决2维空间向量的3级分类问题。(Opencv-based support vector machine (SVM) of the code, the use of SVM to solve 2-dimensional vector space of three classifications.)

实现图像的相位相关匹配，该算法有一定的优点于其他算法相比。(images related to the phase matching, the algorithm has certain advantages compared to other algorithms.)