CSC.EGBIS.JSEG.Meanshift

KLT point match:Detection and Tracking of Point Features.

打开24位彩色bmp文件, 显示该图像 将图像内容顺时针旋转90度后显示出来 将图像分成等大小的4块，将第1和第3块像素互换后保存 将旋转后的图像转换成灰度图像显示，并保存 对灰度图像求Sobel边缘图，显示出来，并保存 对灰度图像进行Gaussian平滑，并保存（需要体会平滑的作用） 对灰度图像进行2值化(Open 24-bit color bmp files, displays the image will rotate clockwise image content displayed image is divided into four equal-sized 90 degrees, the first and three pixels after swap to save the rotated image conversion ashes of the image display, and save images to grayscale seeking Sobel edge map is displayed, and save the gray image Gaussian smoothing, and save (experience required smoothing effect) grayscale image binarized)

图像亮度和对比度调节，已验证，分别有亮度调节和对比度调节的调整框(Image brightness and contrast adjustment, has been verified, respectively, brightness adjustment and contrast ad)

CCD 摄像机内外部参数快速准确的标定方法(Fast and accurate calibration method for internal and external parameters of CCD camera)

：植物种类识别方法主要是根据叶片低维特征进行自动化鉴定。然而，低维特征不能全面描述叶片信息，识别准确率低，本文提 出一种基于多特征降维的植物叶片识别方法。首先通过数字图像处理技术对植物叶片彩色样本图像进行预处理，获得去除颜色、虫洞、 叶柄和背景的叶片二值图像、灰度图像和纹理图像。然后对二值图像提取几何特征和结构特征，对灰度图像提取 Hu不变矩特征、灰 度共生矩阵特征、局部二值模式特征和 Gabor 特征，对纹理图像提取分形维数，共得到 2183 维特征参数。再采用主成分分析与线性 评判分析相结合的方法对叶片多特征进行特征降维，将叶片高维特征数据降到低维空间。使用降维后的训练样本特征数据对支持向量 机分类器进行训练(plant species identification method is mainly based on blade automatic identification of low dimensional characteristics.However, can not fully describe blade low-dimensional feature information, identification accuracy is low, in this paper A kind of plant leaves recognition method based on multiple feature dimension reduction.First by digital image processing technology to the plant leaf color sample image preprocessing, obtain background color removal, wormhole, petioles, and the blades of a binary image, gray image and texture image.Then the binary image to extract the geometric characteristics and characteristics of structure and characteristics of gray image extraction Hu moment invariants, gray co-occurrence matrix feature, local binary pattern features and Gabor, to extract the fractal dimension of texture image, get 2183 d characteristic parameters.By principal component analysis and linear uation analysis method of combining the characteristics of blade more feature dimensi)

改程序就代码可以找出从不同角度或区间的两幅遥感影像的同名点(Change the program code can find it from different angles of the same name point or interval of two remote sensing images)

VC做的图像处理方面的一些代码，仅供参考(VC do image processing of some code, only supplies the reference )

该VC++程序是基于CUDA架构的中值滤波程序，GPU加速，并且使用了opencv函数库(The VC++ program is based on the CUDA architecture median filtering program, GPU acceleration, and use the opencv library)

说明：  基于边缘特征的SAR图像与光学图像匹配，测度为Hausdorff距离(SAR images based on edge features and optical image matching, for the Hausdorff distance measure )

在GPU-CUDA平台上进行SIFT特征提取，加快提取速度(On GPU-CUDA platform SIFT feature extraction, speeding up the extraction rate)