i---retinex

楔波变换，在SAR图像中实现边缘检测，为目标识别做铺垫工作。(The wedge waves transform, SAR image edge detection, target identification pave the way for the work.)

灰度图像的属性计算：利用bwlabel和regionprops函数对度量二值图像中目标对象的属性。(Attribute gray image: Using bwlabel and regionprops function measure binary image of the target object attributes.)

说明：  直方图均衡，图像去雾处理，是把原始图像的灰度直方图从比较集中的某个灰度区间变成在全部灰度范围内的均匀分布。直方图均衡化就是对图像进行非线性拉伸，重新分配图像像素值，使一定灰度范围内的像素数量大致相同。(Histogram equalization, image processing to the fog, is the original image histogram to a gray scale from the more concentrated into the full range of uniform distribution within the gray area. Histogram equalization is that the image is non-linear stretch, re-distribution of the image pixel values, so that a certain number of pixels within the gray area roughly the same.)

FMCW雷达测距的信号处理技术研究 非常好的资料(FMCW radar ranging signal processing technology research)

说明：  水平集图像分割方法中的窄带技术的MATLAB代码实现(Level set image segmentation methods narrowband technology MATLAB code)

基于radon的图像运动模糊参数估计程序，估计了模糊角度与模糊尺度，但过大的图片需先处理后才能使用(Radon-based image motion blur parameter estimation procedure, estimates of the fuzzy point and fuzzy scale, but the picture is too large to be treated before use)

对雾霾天气的图像进行初步的去雾处理，基于双边滤波算法(The screen image of haze weather preliminary to deal with the fog, based on bilateral filtering algorithm)

校正图像倾斜的程序，很好用，可以纠正几何投影变形(Image tilt correction procedures, very good use, you can correct the distortion geometric projection)

绣花问题是连续型的填充，在不同区域的缝制过程中，缝针不能提针，因此不能用一般的离散型区 域填充方法处理。本文运用几何计算和图论理论提出了一个绣花缝针轨迹自动生成算法：先对轮廓走向进行 定义，通过轮廓铅垂方向的局部极值点的分割线将图案从上向下进行分割，采用交点的特征值比较彻底的解 决了分割时的重点问题，将图案区域准确的划分成缝针能一次完成的若干个节点。在此基础上根据节点的邻 接关系建立节点的邻接“图”，通过图论中半哈密尔顿路径或深度遍历方法找到节点的遍历（缝制）序列和每 个节点的缝制方向，最后可对设定的起点、终点和缝针间隔的条件自动提供缝针的走向轨迹。(In the process of embroidering, needle can not hang up for changing to a different area. Therefore, Embroider problem could be abstract as a continuous area-filling work. Considering disperse area-filling methods can not process this problem well. Based on geometry computing and graph theory, an algorithm of finding path of embroidering needle are proposed in this paper. First, outline orientations are defined, and finding all local extreme points of inner outline on their gravitational orientation to build sectioning lines so as to divide the picture. By using intersection point character the overlap point problem was solved perfectly. Therefore, the picture is divided into some nodes which can be finished alone. Then, based on connections of these nodes, an adjacency graph of nodes was built. Using half-Hamilton path or depth-first search method, both embroidering sequence and direction of these nodes could be got from the graph. Finally, from a defined start-point, end-point)

说明：  计算图像峰值信号比，比较边缘检测图像的质量(Calculate the image peak signal ratio and compare the quality of edge detection)