数学建模运动模糊图像的复原

将一个图像的感兴趣区域替换到另一张图像的相同区域中(Will replace the region of interest of an image to another image of the same region of the)

MATLAB 编写的两种将灰度图二值化（多值亦可）的源程序，并付word说明。(it contains two methods which can change gray image to binary image (or multivalue image )in segments.)

对RGB图象的处理,一般要进行增强以达到去噪,锐化的功能,本程序在拉普拉斯算子基础上实现的(RGB images of the treatment, the general should be enhanced in order to achieve de-noising, sharpening function, the procedures in the Laplacian, based on the)

说明：  对图像进行伽马校正，可以有效提升图像 亮度和对比度，低于低照度图像现在小于1的参数，对于高亮度的图像选择大于1的参数可以有效调节图像亮度。(Gamma correction can effectively improve the brightness and contrast of the image. The parameters lower than the low illumination image are less than 1. For the high brightness image, the selection of parameters greater than 1 can effectively adjust the brightness of the image.)

此程序利用openCV中人脸识别于模版匹配实现机器人的运动控制功能，其中机器人控制用了Aria的库和模拟器，使用者可根据控制需要替换这部分程序。 本程序的核心部分一直用于只能轮椅的人脸控制。(This process us face recognition in openCV and template matching to achieve robot motion control functions, which used the Aria library and robot simulator, user need replace this part of the control procedures to achieve their application.)

基于Harris角点检测的图像拼接matlab实现， 主要内容包括Harris角点检测，NCC,RANSAC以及2幅图像的拼接(A image mosaicing algorithem which based on Harris corner feature detection achieved in matlab. The main contents include the Harris corner detector, the NCC, the RANSAC and two image mosaicing)

此程序用于伪彩色图象的处理，实现程序的增强功能．(procedure for the pseudo-color image processing, and process enhancements.)

IEEE CSVT 2001的一篇关于颜色直方图法的论文,彩色图片的颜色特征提取算法的代码.(IEEE CSVT 2001 an article about color histogram method paper, color the picture color feature extraction algorithm of the code. )

hough和randon函数求图像中圆，对于水中气泡检测效果很不错(Circle detection based on random Hough transform)

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.)