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图像配准，利用互相关的方法进行图像配准，能达到良好效果(Image registration, the use of the cross-correlation method of image registration, and can achieve good results)

YUV多种图像处理方式，包括yuv2rgb,rgb2yuv.等等。但需要仔细调试(YUV multiple image processing methods, including yuv2rgb, rgb2yuv. And so on. But needs to carefully debugging)

这是个criminisi算法的源码，可以对图像进行相应的修补。效果很好。(This is a criminisi algorithm source code, images can be appropriate patch. With good results.)

HOG特征提取，以通过测试。希望对大家能有所帮助。(HOG feature extraction, in order to pass the test. I hope we can help.)

说明：  图像处理，通过图像融合技术，可以实现将多幅来自同一场景的图像，利用其冗余信息，融合成一幅比原来任何一幅都易于为人们所理解的图像，同时可供人们进行进一步的观察和处理(Through image fusion technology, it can realize the fusion of multiple images from the same scene, and make use of its redundant information to form an image that is easier to understand than any original image)

这段代码使旋转、翻译和规模algoritms一些图像使用绘图对象(This code enables rotation, translation and scale algoritms some images using the drawing object)

各个坐标系之间的坐标变化：地心大地坐标到地心空间大地直角系，地心系和测站系，测站系和测站系等之间的变化，旋转，平移。(Coordinate changes between the various coordinate systems: geocentric geodetic coordinate system to the geocentric Cartesian space earth, geocentric system and station lines, change the station, such as lines and lines between stations, rotation, translation)

说明：  图像去雾可以还原图像的颜色和能见度，同时也能利用雾的浓度来估计物体的距离，这些在计算机视觉上都有重要应用(Image Fog can restore the color and visibility of the image, but also can use the concentration of the fog to estimate the distance of the object, which have important applications in computer vision)

（1）计算图像中每个像素点的LBP模式(等价模式,或者旋转不变+等价模式)。 （2）然后计算每个cell的LBP特征值直方图，然后对该直方图进行归一化处理(每个cell中，对于每个bin,h[i]/=sum,sum就是一副图像中所有等价类的个数)。 （3）最后将得到的每个cell的统计直方图进行连接成为一个特征向量，也就是整幅图的LBP纹理特征向量； 然后便可利用SVM或者其他机器学习算法进行分类识别了。((1) calculate the LBP pattern of each pixel in the image (equivalent mode, or rotation invariant + equivalent mode). (2) then the LBP eigenvalue histogram of each cell is calculated, and then the histogram is normalized (for each cell, for each bin, h[i]/=sum, sum is the number of all the equivalent classes in a pair of images). (3) finally, the statistical histogram of each cell is connected into a feature vector, that is, the LBP texture feature vector of the whole picture. Then, SVM or other machine learning algorithms can be used for classification and recognition.)

I WANT SOURCE CODE FOR IMAGE SEGMENTATION