Hyperspectral-Data-Classification

采用National Instruments 视觉算法库，雷赛运动控制卡，映美精相机 检测手机LOG(Using National Instruments vision algorithms library, Lemire motion control card, Imaging camera detects the phone LOG)

说明：  边缘特征的提取就是求图像梯度的局部最大值和方向。实际计算中，以微分算子的形式表示，并采用快速卷积函数来实现。常用的算子有微分算子，拉普拉斯算子，Canny算子等。其中Canny边缘检测是一种较新的边缘检测算子，具有较好的边缘检测性能，得到越来越广泛的应用。Canny边缘检测法利用高斯函数的一阶微分，它能在噪声抑制和边缘检测之间取得较好的平衡(Edge feature extraction is to seek the local maximum of image gradient and orientation. The actual calculation to the form of differential operator representation, and using fast convolution function to achieve. Commonly used operators are differential operators, Laplace operator, Canny operator and so on. Canny edge detection which is a relatively new edge detection operator, and has good edge detection performance, get more and more widely used. Canny edge detection method using first derivative of Gaussian function, it can in the noise suppression and edge detection to achieve a better balance between)

使用snake算法寻找图形的轮廓，GVF梯度代替传统方法取得了很好的效果。(Snake algorithm to find the outline of the graphics， GVF gradient instead of the traditional methods achieved good results.)

了解直线拟合、平面拟合的方法 掌握用随机抽样一致 算法实现平面提取(A method of understanding straight line fitting and plane fitting Grasp the random sampling consensus algorithm for planar extraction)

车型识别,根据surf算法特征匹配实现大型车、小型车的识别。(automotive style recognition)

模糊图像去模糊处理，Amit等人发表的模糊核的估计算法，图像去模糊，得到清晰图像(image deblurring by Amit)

对于一张8位灰度图像lena.bmp 1）运用4×4抖动矩阵，生成对应抖动图像 2）生成有序抖动图像 3）对于一张24位彩色图像，生成4×4抖动图像( For a 8-bit gray image (lena.bmp) 1）Use a dithering matrix (4*4), generate the dithered image. 2) Generate the ordered ditering image (4*4). 3) For a 24-bit color image, generate the dithered image (4*4). )

说明：  图像处理中应用非常广泛的二维最小均方误差算法（TDLMS）。绝对好用！(Image Processing is widely used two-dimensional MMSE algorithm (TDLMS). Absolute ease of use!)

线性变换，如图像的拉伸变换等，调试通过，简单易学(Linear transformation, such as image stretching transformation, debugging through easy to learn)

雷达信号处理一些相关操作，计算其距离向，方位向以及多普勒参数等。(radar signal processing)