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图象分割程序：先用梯度函数进行边缘检测,然后二值化后分割图象(Image segmentation process: first the gradient edge detection function, and then after binarization image segmentation)

Tracking based on background subtraction

形态学图像增强算法，包括对比度增强和边缘锐化(Morphological image enhancement algorithms, including contrast enhancement and edge sharpening)

一种基于景深的去雾方法，将按通道中的最大值和最小值作为景深基准线，计算其垂直方向上的暗通道像素均值作为透射图，实现去雾，对航拍图效果显著(A dehaze method based on the depth of field, draw a depth datum line according to the maximum value and minimum value of the dark channel, calculate the pixel of the dark channel at the line perpendicular to the depth datum line.Then the transmission map has been gotten. This method performs good especially when processing the aerial map.)

一种基于改进DRLSE的运动目标分割方法,为了得到精准、连续的运动目标轮廓，提出将帧间差分法和改进的距离规则水平集演化(DRLSE)方法结合应用于运动目标分割。(In order to get an accurate and continuous contour of moving target, a novel method to segment moving object by combining the frame difference and an improved distance regularized level set evolution (DRLSE) is proposed. )

本代码是用Matlab实现图像的超分辨率重建，方法为凸集投影法，能从多幅低分辨率图像重建一幅高分辨率图像。(We use Matlab to reconstruct image. The method is convex projection on suoer-resolution(POCS).)

这是基于VC++编写的对遥感影像分析的程序，主要是对遥感影像进行PCA变换，使得对影响分析不仅可以依托于现成软件，我们自己也可以开发(This is written in VC++ based on remote sensing image analysis program, mainly for remote sensing images PCA transform, makes impact analysis can not only rely on ready-made software, we can also develop their own)

将图片转化为BMP位图，然后通过逐行扫描识别图片中的数字。(A picture into a BMP bitmap, and then through the progressive scanned image in the figure.)

盲去卷积，实现图像的高分辨 准确估计模糊核(a novel scale-invariant regularizer that compensates for the attenuation of high frequencies and therefore greatly stabilizes the kernel estimation process.)

提出了一种基于图像边缘连接的线段检测方法。数字图像中的线段是由很多线段图元组成,在同一 条线段中,它们的方向是相同的并且受到真实线段的方向约束。因此可以通过提取小的线段图元, 然后分析它们 的连接特性, 进行线段的检测。首先用ADM 算法对图像进行边缘检测, 得到单像素宽的边缘 然后在4 个方向上 进行线段的检测 对初步得到的结果进行合并和验证, 去掉短的线段, 连接临近的线段。经过实验证明, 该方法能 够快速地提取图像中的线段,并且对噪声具有一定的鲁棒性(A line segment connecting a detection method based on image edges. The segment of the digital image is composed by many segments elements, their orientation is the same and by the real line segment direction constraint in the same segment. By extracting a small segment Element can then analyze their connection characteristics for the detection of the line segment. First with ADM algorithm for edge detection on the image to obtain a single-pixel-wide edge then in the four directions on the detection of the line segments merger and verification of the preliminary results obtained, removing the short line segments, the line segments connected near. The experiments show that this method can quickly extract the line segments in the image, and certain robustness to noise)