Correlation-Filters-Tracking

锐化效果显示图像 例子

自编图像处理M文件，经过图像增强滤波去噪二值化，边缘提取，实现对图片内物体的生产标准监测(Self image processing M-file, and after image enhancement filter denoising binarization, edge extraction, the production of objects within the picture of standard monitoring)

利用数学形态学的原理实现图像处理，包括腐蚀、膨胀、开、闭运算(The principle use of mathematical morphology realize image processing, including corrosion, swelling, open and close operation)

在大图中找小图

实现峰值信噪比的算法，用于判断图片质量的好坏！十分有用！(Achieve peak signal-to-noise ratio (PSNR) algorithm for judging image quality! Very useful!)

先将字符串转化为像素图，再将像素图还原成二维数组。将二位数组转化为布尔数组。然后用一个顺序结构，第一帧放入比较程序，即显示汉字并闪烁程序。第二帧循环移位程序。第三帧屏幕关闭程序。(First string into a pixel map, and then reduced to a two-dimensional array of pixel map. The two-digit group into a Boolean array. Then a sequential structure, comparing the first frame into the program, the program that displays characters and flashes. The second frame cyclic shift procedure. The third frame of the screen to close the program.)

说明：  RAT power toy (KOL)

说明：  图像的重心区域检测 matlab程序实现 可以检测重心区域并设置成希望颜色，对单景物背景图像效果极佳(regional focus image detection Matlab program can detect regional focus and set hope that the color of single features excellent background images)

用SVD算法实现图像滤波去噪处理，提高图像的信噪比。(SVD algorithm using image processing filter to improve image quality.)

手持式摄像机在使用时常常会受到使用者有意无意抖动的影响,从而影响成像效果，造成录制视频的不稳定及跳动问题，尤其是在使用者在一场景中特写或者跟踪某一具体目标时，使用者通常不能准确定位到或者估计出运动目标的位置，从而造成目标在视频中位置的不稳定，造成视频的主观效果变得不理想。 为了解决这一问题，我们需要设计一种算法来识别这种无意义的运动并设法通过补偿的方式来使得场景中的目标物体保持位置稳定的状态。 手持式摄像机捕获的视频通常都会受到抖动的影响，这严重的影响视频的主观效果。 这里提出的算法可以可靠的用于数字视频的去抖动。这个算法通过识别这些意外的抖动并且利用运动补偿的方法来获得一个较好的视频输出。 这个系统可以分为三个模块：（1）运动估计模块；（2）抖动识别模块；（3）运动补偿模块。 注：代码在matlab 7.7.0(R2008b)运行通过 [1] F Vella, A Castorina, M Mancuso. Digital image stabilization by adaptive block motion vectors filtering, IEEE Transactions on Consumer Electronics, 2002(Handheld cameras are often used by the user intentionally or unintentionally, the influence of jitter affect the imaging results, resulting in instability and beat the problem of recording video, and especially in the user in a scene close-up or tracking a specific target,users often can not accurately navigate to estimate the location of the moving target, resulting in the subjective effects of target location of the instability in the video, resulting in video not ideal. In order to solve this problem, we need to design an algorithm to identify such a meaningless exercise and try to make the object in the scene to keep the position stable state by way of compensation. The handheld camera captured video usually subject to the influence of jitter, the subjective effect of which seriously affect the video. The algorithm proposed here can be reliably used for digital video to jitter. This algorithm by identifying the jitter of these accidents and the use of motion compensation m)