GUI

说明：  SIFT用于图像全景拼接的源码，内附算法描述，很好用。(SIFT source code for image panorama stitching, containing algorithm descriptions, easy to use.)

中值滤波，对3X3有优化，纯C，正对BMP格式(Median filtering, there are optimized for 3X3)

在高斯混合噪声背景下实现SLIM谱估计算法和l1范数SLIM谱估计法，并在-5到15的信噪比条件与CRLB对比均方频率误差(the paper achieves the SLIM spectral estimation algorithm and l1-SLIM spectral estimation method under the Gaussian mixture background noise,then compares the mean square frequency error with CRLB under SNR from-5 to 15 )

该程序采用总变差方法去除图像噪声，希望大家喜欢(the procedure used to remove the deteriorating image noise, hope you like)

文章对比分析了火焰不同的形状结构特征，及其特征组合对火焰检测有效性的影响，提出了一种融合圆形度、矩形度和重心高度系数的火焰检测算法，然后将融合后的火焰特征输入支持向量机(SVM)中进行分类( Based on fusion of these flame features，the support vector machine (SVM) is used for classi- fication． Experimental results on the fire videos at Bilkent University show that the proposed algorithm is efficient and fast for fire detection，and it could detect fire real-time under a variety of circumstances．)

说明：  摄像头条形码识别，可以发送命令识别后，展示识别码质量(ShopSavvy Barcode Scanner)

案例推理,用于匹配,欢迎大家交流,有资源共享,(Case-based reasoning for matching, welcomed the U.S. exchange, resources sharing,)

这是本人发表的目标跟踪方面论文使用的代码，是基于随机假设概率滤波的多目标跟踪算法。(This is the code used by the target tracking paper I published, filter multi-target tracking algorithm based on the probability of a random assumption.)

通过纹理方向估计消失点，通过消失点来检测道路区域。 该程序应用到了基于纹理的张量投票算法来估计消失点；通过纹理方向和颜色信息，生成用于估计两个最主要道路边界的直方图；最后将道路区域定义为两个检测到的道路边界之间且低于估计的消失点的区域(The vanishing point is estimated by the texture direction, and the road area is detected by the vanishing point. The program applies a texture-based tensor voting algorithm to estimate the vanishing point; through the texture direction and color information, generates a histogram for estimating the two most important road boundaries; finally defines the road area as two detected road boundaries. An area between and below the estimated vanishing point)

适合初学小波的同志，小波图像增强原理底层。严格高低频分解重构，没有使用小波工具库。(Suitable for beginners wavelet comrades, the underlying principle of wavelet image enhancement. Strict high-low-frequency decomposition of reconstruction, did not use the wavelet tool library.)