rectangular-in-multi-goal-picture

SAR成像中的RD算法是最经典的校正算法之一，提供的代码有详细的注释和说明，欢迎大家下载学习(RD SAR imaging algorithm is one of the most classical calibration algorithm, the code provided detailed notes and descriptions, are welcome to download the study。)

db4小波的提升小波分解，从已发表的论文中得来，可放心使用(db4 wavelet lifting wavelet decomposition, the published papers come, you can be assured)

说明：  用VC开发的图形填充算法，简单实用， 希望对你的图形开发有所帮助， 如果有什么问题，可以与我联系(development of the VC graphics filling algorithm, simple and practical, and I hope to your graphics development will help, if any, can contact me)

图像拼接，用于合成全景图像，VC++开发环境，C++实现。(Image Stitching)

通过高通滤波器实现对图像的锐化处理，能去除不需要的模糊轮廓而加强边缘的对比度。(Image sharpening to achieve through a high-pass filter, and enhance the contrast edges blurred outline can remove unwanted.)

说明：  基于背景差分法和帧间差分法的目标跟踪 应用了二维滤波，效果较好(Based on background difference and frame difference method applied to two-dimensional target tracking filter, better)

对于叶片面积的计算，进行图像预处理，灰度转换、直方图、去噪声等，最终计算出叶片面积的像素和。(For the calculation of leaf area, image pre-processing, gray-scale conversion, histogram, to noise, etc., and ultimately calculate the leaf area and the pixels.)

基于神经网络的地面裂缝检测软件，可以在界面上选择各种功能去检测。(Ground crack detection software based on Neural Network)

说明：  通过matlab源码实现图像的最佳自动阈值分割，所选算法是常见的大津法(Matlab source code through the realization of the best automatic image thresholding, the selected algorithm is a common method of Otsu)

　对经典的二值化方法Ostu 算法和Bernsen 算法中存在的缺点进行了分析, 提出一种结合Canny 算子的图像 二值化方法.该方法综合考虑了边缘信息和灰度信息, 通过边缘附近种子点在高阈值二值化图像中的填充和低阈值 图像对它的修补而得到二值化结果图像, 较好地解决了经典二值化方法中存在的抗噪能力差、边缘粗糙、伪影现象 等缺点.实验结果证明, 该方法能够较好地解决低对比度图像和目标像素灰度不均匀图像的二值化问题(The disadvantage of the classical binary method Ostu Bernsen algorithm and algorithms exist were analyzed, one binding Canny operator image binarization method. This method considers the edge information and gray information, through seed near the edge point padding and a low threshold image to its repair in a high threshold binary image to obtain a binary result image, it solves the noise immunity classical binary method exists difference, rough edges, artifacts phenomenon and other shortcomings. the experimental results show that this method can solve the low-contrast image and the target image pixel gray uneven binary problem)