Pictures

说明：  为了在抑制噪声时尽可能保留图像边缘信息，提出一种自适应各向异性高斯滤波器设计方法. 该方法由独立 强度传播（IDS）模型决定滤波器的长轴尺度，由像素的邻域平滑度决定长短轴的比例，然后根据该处的灰度梯度方 向自适应决定各向异性滤波器的长轴方向. 仿真实验表明，提出的自适应各向异性滤波器具有很强的噪声抑制和 边缘保持能力. (In order to suppress noise, as far as possible to keep the image edge information, an adaptive anisotropic Gaussian filter design methods. The method by the independent strength spread (IDS) model determines the long axis of the filter scale, the pixel neighborhood smoothness determine the ratio of minor axis, and then there' s gray gradient direction of adaptive decision the long axis of anisotropic filter. Simulation results show that the proposed adaptive anisotropic filter has a strong noise suppression and preserve edges.)

说明：  利用区域标记进行区域分割，去除面积较小的联通区域(Use of regional segmentation markers, removing smaller areas Unicom)

说明：  使用matlab中的nlfilter来进行邻域处理(Using nlfilter in MATLAB to process neighborhood)

说明：  image 数组 高速读写 不用指针(image array IO C#)

VC图像编辑软件 就要卷积模糊和卷积模糊加噪 以不同方法（大于等于2）实现图像的模糊效果（局部或全局）。并以BMP格式存储。(soft)

利用python和opencv拼接两张图片(Splicing two pictures using Python and opencv)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

基于bp神经网络的车牌字符识别源程序，采用字符比对的方式进行切割(The structures of the neural networks were designed using a constructive algorithm where the basic idea was to start with a small network,then add hidden units and weights incrementally until a satisfactory solution be found .The higher efficiencies were for a 30×17×10 number network and letter network)

共厄梯度方法!!!本程序适用于求解形如f(x)=1/2*x Ax+bx+c二次函数的稳定点； (total Eritrea gradient method! ! ! The procedure will be applicable to solve the shape of f (x) = 1/2* x Ax bx c quadratic Function stability;)

实现图像配准和计算配准均方根误差的功能，人工选取控制点，包括四种转换方法。(Achieve image registration and registration RMSE calculation function, manual selection control points, including four kinds of conversion methods.)