lane_detection

小波算法。机械化的提高我们的效率。让我们减少错误率。大家要对她有性心。(Wavelet algorithm. Mechanization to improve our efficiency. Let us reduce the error rate. We have to have sex to her heart.)

图像分割关系到目标识别的精度，是目标检测的关键一步，其中提供了一些图像分割的代码，主要为otsu算法的分割方法，很实用(s related to the accuracy of target recognition, image segmentation is a critical step in target detection, provides some image segmentation code, very useful)

sar图像变化检测 基于减法代码 比较两幅图片的细微差别(sar image change detection code based on subtraction of two pictures comparing the nuances of)

在图像处理中实现带通滤波器的功能的matlab实现代码(Bandpass filter)

不均匀光照下的文字分割，综合运用同态滤波方法、Bernsen局部阈值法、边缘识别法。(Uneven illumination of the text segmentation, integrated use of homomorphic filtering methods, Bernsen local threshold, the edge identification method.)

对图像进行平滑去噪，提高图像的质量，为后期的图像处理打基础(very good)

编程实现二维8*8图像块的DFT，DCT变换 输入一副RGB图像，将其转化为YCbCr颜色空间，然后对Y分量做分块DFT变换，保存为灰度图像，统计计算时间 编程实现8*8块DCT变换,然后分别显示，当使用64个DCT系数里面的一些系数进行重构，比较其质量；同时熟悉采用FFT来实现DCT变换的思想，并显示2维8*8DCT变换的基函数图像(Programming the DFT, DCT transform of two dimensional 8*8 image block Input a pair of RGB images, transform it into YCbCr color space, then divide the Y component into block DFT transform, save as gray image, and calculate the calculation time The 8*8 block DCT transform is implemented by programming, and then it is shown that when using some coefficients in 64 DCT coefficients, the quality is reconstructed. Meanwhile, the idea of DCT transformation is familiar with FFT, and the base function image of the 2 dimensional 8*8DCT transform is displayed.)

说明：  实现 %1、利用RGB模型识别天空区域；2、利用边缘识别检测天空边缘分割线；3、利用预测边缘点和实际边缘点的周围区域的均值滤波与本边缘点下方的像素之间的差异大小来修正天空边缘分割线 %4、将sky_seg+depthmap_v2中多余的带注释的地方删掉了 %！！！记得在295行，一定要改动是用I6还是I7，如果用sky_initia(f = edge(double(BW),'canny',thresh,sigma);)

图像处理课程设计——《人脸识别》，用matlab实现的，代码加实现，以及设计报告(Image processing designation of face recognize.)

一个车牌字符分割小程序，分割效率高。实现简单(A license plate character segmentation of small procedures, segmentation and high efficiency. Realize a simple)