Hilbert-transform

STM32F103开发板，HC-SRO4超声波测距模块

主要是多光谱多波段两幅图像的变化检测求得差异影像 大家可以参考参考 运行主程序(mian is used to difference of two images)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)

利用稀疏表示进行图像去噪时，需要生成两种学习字典，该源码比较了生成的两种字典的优劣(Denoising sparse representation, it is necessary to generate two learning dictionary, which compares the generated source code of the merits of two dictionary)

利用最佳直方图熵法（KSW熵法）及穷举法实现灰度图像阈值分割(The best the histogram entropy method (KSW entropy method) and the brute-force method to achieve gray image threshold segmentation)

基于平稳小波变换的图像融合。低频分量取平均，高频分量取绝对值最大。最后做逆平稳小波变换。(stationary wavelet transfrom.Averaged low frequency components, high frequency components of the maximum absolute value. Finally, do the inverse stationary wavelet transform.)

图片文字 合成实例

批处理的练习题，实验过程，命令的意义及实验截图(Batch exercises, experimental procedure, meaning command and experimental shots)

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.)

讲解了shearlet变换在图像融合中的应用(Explained shearlet transform in image fusion)