test3

小球沿斜线运动,可以扩展到其他程序中，第一次上传，谢谢。(a ball along with a line.)

一种基于non-sample的纹理合成demo，程序性能还有待优化，效果还不错.(texture synthesis demo.)

说明：  本程序使用MFC编写了一个能够在同一界面上显示立体图形的三视图的源程序。(This program using MFC wrote a can in the same interface shown on the SanShiTu three-dimensional graph of the source program.)

微波遥感集中实习SAR影像几何校正，微波遥感几何校正(geometric correction of SAR)

sift 的c++代码。。。。。。。。。。。。(sift c++ code)

打开BMP图像 IHS Brovey图像融合(Open the BMP image IHS Brovey Image Fusion)

该程序能够实现图像的二值化，基于C语言的。实现的效果很好(The program to achieve a binary image, based on C language. Achieve a good effect)

天津工业大学课程设计，内容包含vs2010对图像的灰度化，二值化，边缘检测。包含单纯c语言编写的对图像的灰度化，二值化，边缘检测的一个.C文件，可以直接用vc6.0运行，也可以直接在DSP上运行，还包含一份详细的设计报告。(Tianjin Polytechnic University curriculum design, content includes vs2010 grayscale image binarization, edge detection. Contains pure c language for image graying, binarization, edge detection is one. C file that can be run with vc6.0 can also be run directly on a DSP, also contains a detailed design report.)

1、参数初始化； 2、形成边界削波数据； 3、波场初始化； 4、Zmax层波场延拓到深度Zmax-1； 5、Zi+1层波场延拓到深度Zi； 6、重复5，从Iz Nz-1开始，直到Iz 1，得测线上的频率—空间域波场； 7、频率-空间域波场对频率做反傅里叶变换，得时间-空间波场； (1, parameter initialization 2, the formation of boundary clipping data 3, wave field initialization 4, Zmax layer wave field extended to the depth of Zmax-1 5, Zi+1 layer wave field extended to the depth of Zi 6, repeat 5, starting Iz Nz-1 until Iz 1, the frequency of the test line- spatial domain wave field 7, frequency space domain wave field to frequency inverse Fourier transform, time- space field )

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.)