CNN_Edge_extraction

说明：  有关图像处理中的图像校正，MATLAB，亲测可行(ImageRegistration matlab)

高光谱图像的解译是遥感图像应用的一个重要环节。基于线性光谱混合模型的光谱解译技术正在越来越广泛地应用。仿真结果表明，当部分端元参与解译和分区域进行解译时，高光谱图像的解译效果会得到较显著改善。(The unmixing of Hyperspectral imagery is a critical link of the application of remote sensing imagery. Based on linear spectral mixture model, spectral unmixing technology now is being increasingly used. On the basis of it,studying unmixing ways engaged by endmembers in different conditions, comparing and discussing a more effective expression mode of endmembers.)

一种比较新颖的方法，通过对以往提出几种核估计方法的融合，建立新核，达到更好的图像恢复效果(A relatively new method, proposed in the past by the nuclear fusion of several estimation methods, the establishment of new nuclear, to achieve better image restoration effect)

说明：  镜头指纹识别，提取镜头特征，对其他照片进行识别，判断是否来源同一相机。(Image Source Detection)

通过多分辨率分解，实现红外图像的增强，改善图像的对比度(Through a multi-resolution decomposition, to achieve enhanced infrared image)

操作简单，实现双目视觉下的三维重建，输入双目下两张图片，生成渲染后的重建结果。(Simple, to achieve a three-dimensional reconstruction under binocular vision, binocular enter under two pictures, generated reconstructions rendered.)

图像处理中的数学修炼

说明：  一个基于样例的图像修补技术的matlab演示(A sample-based image repair technology demo matlab)

matlab 车牌识别，含有gui界面，边缘检测车牌定位，神经网络字符识别(Matlab license plate recognition, including GUI interface, edge detection, license plate location, neural network, character recognition)

针对可见光与红外图像的特点和难点，提出了可见光与红外图像配准与融合中的关键技术，即: 使用新型的基于一维最大类间方差和最大连通性测量的图像分割方法对源图像进行分割来更好地实行图像粗 配准 使用新型的特征点提取方法，特征点的匹配及误匹配的消除来更好地实行图像精配准 采用新型的基 于区域的树状小波活性测度计算来实现树状小波图像融合 利用自生成神经网络来实现模栩图像融合. (For visible light and infrared images of the characteristics and difficulties, a visual and infrared image registration and integration of key technologies, namely: the use of new one-dimensional based on the largest variance between-class connectivity and the largest measuring method of image segmentation source image segmentation to better implementation of coarse image registration the use of a new type of feature point extraction method, feature points of the match and the elimination of false matches to better the implementation of image fine registration the use of new tree-based wavelet calculated to measure the achievement of the activity tree wavelet image fusion the use of self-generating neural network to achieve image fusion Xu mode.)