IDl

使用基于词典的稀疏表示高光谱图像分类,多任务联合稀疏表示和逐步MRF优化的高光谱图像分类(Dictionary-based sparse representation hyperspectral image classification, multi-task joint sparse representation and stepwise MRF optimized hyperspectral image classification)

说明：  图像融合中的平均梯度、相关系数、信息熵、交叉熵、联合熵、均方误差、互信息、信噪比、峰值信噪比、均方根误差、空间频率、标准差、均值、扭曲程度、偏差指数等等(Average gradient, correlation coefficient, information entropy, cross-entropy, joint entropy, mean square error, mutual information, signal-to-noise ratio, peak signal-to-noise ratio, root mean square error, spatial frequency, standard deviation, mean, distortion degree, deviation index, etc. in image fusion)

使用Harris角点检测方法进行图像特征点提取,NCC描述的方法进行粗匹配,再使用RANSAC算法进行精匹配。(Using the Harris corner detection method to extract the feature points of the image, the NCC description method performs rough matching, and then uses the RANSAC algorithm for fine matching)

C# 窗口捕捉 句柄 实例源码下载

基于MATLAB环境的图像水印攻击试验源程序(MATLAB-based image watermarking attacks environment test source)

天津工业大学课程设计，内容包含vs2010对图像的灰度化，二值化，边缘检测。包含单纯c语言编写的对图像的灰度化，二值化，边缘检测的一个.C文件，可以直接用vc6.0运行，也可以直接在DSP上运行，还包含一份详细的设计报告。(Tianjin Polytechnic University curriculum design, content includes vs2010 grayscale image binarization, edge detection. Contains pure c language for image graying, binarization, edge detection is one. C file that can be run with vc6.0 can also be run directly on a DSP, also contains a detailed design report.)

一种细化的骨架提取算法 可以提高徐璈的处理厚重图像(sgsdgsdgsdgggs skeleton extraction)

对图像进行二维离散小波变换, 变换级数大于等于3级,然后进行阈值化处理(阈值约为10左右),再统计系数中0的个数（百分比表示）并进行重构, 最后计算重构图像的峰值信噪比(PSNR). (Two-dimensional discrete wavelet transform image transformed series is greater than or equal to 3, and then processing thresholding (threshold of about 10 or so), then statistical coefficient in the number (expressed as a percentage) and to reconstruct the final calculation reconstructed image of the peak signal-to-noise ratio (PSNR).)

说明：  程序功能是把一副倾斜的文字图像矫正过来，通过边缘检测再进行霍夫变换完成(The program function is to correct a skewed text image.)

说明：  遥感信息工程学院遥感原理与应用课程实习监督分类(Supervised of Remote Sensing Principle and Application Course Practice)