fenjiechonggou

NJW算法，普聚类算法，利用3种拉普拉斯矩阵，作用在自制的数据集上(failed to translate)

【实例简介】C#利用baslerSDK实现相机采集图像  采集图像，设置参数

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )

说明：  滤除各种噪声比较，高斯噪声，NLM滤波，双边滤波。(Comparison of filtering out various noises)

说明：  本代码使用MATLAB编写的基于GST模型的红外弱小目标检测代码(% This source code is for infrared small target detection method based on Generalized Structure Tensor (GST). % If you use this code in your publications, please cite:)

对ccd图像进行解码采集，并通过VGA输出(Ccd image decoding of the collection, and through the VGA output)

matlab压缩感知中的一种基于全变分正则化的重建算法——TVAL3(In compressed sensing, a reconstruction algorithm based on total variation regularization- TVAL3)

说明：  snake模型 简单 可以修改迭代次数跟初始mask 挺不错的，可以改参数(snake model Simple can modify iterations with initial mask quite good can change parameters)

基于空间几何约束的单目视觉物体测距 基于空间几何约束的单目视觉物体测距(Geometric constraints based on spatial objects ranging monocular vision Geometric constraints based on spatial objects ranging monocular vision)

很好的流形学习，处理高维数据，降维操作，里面含有LLE，PCA，Dijstra,Iosmap等等(Good manifold learning, processing high dimensional data, dimensionality reduction operations, including LLE, PCA, Dijstra, Iosmap, etc.)