改进RLS校正算法

说明：  图像超分辨是目前国内外研究的热点，该算法主要用于光学图像的超分辨(Image super-resolution is the study of hot spots at home and abroad that the algorithm is mainly used in optical image of the super-resolution)

powell刚性图像配准，c++代码，通过查找非相关方向进行配准.(Polwell rigid image registration, c++ code, by looking for non-related directions for registration.)

说明：  kl变换. KL变换的流程如下： （1)获取多幅图像的统计特性：图像之间的协方差 （2)获取协方差的特征值和特征向量，从而获取正交核:特征矩阵 （3)图像对应象素点对各个特征向量进行投影运算。(kl transformation)

DCT数字水印基于CVI平台。用c编写的。(DCT digital watermarking)

REWIND Project中图像篡改检测工具源代码(Matlab GUI for digital image forensic provided by REWIND Porject)

传统滤波方式如均值滤波，中值滤波，维纳滤波对图像去噪的处理以及自适应中值滤波对图像去噪。(Traditional filtering methods such as mean filtering, median filtering, wiener filtering for image denoising processing and adaptive median filter for image denoising.)

近似熵算法对脑电信号进行特征提取的一些材料(Some materials approximate entropy algorithm for EEG feature extraction)

基于椒盐噪声滤波的改进加权中值滤波算法,目的在于处理高浓度椒盐噪声，并且有效的保护边缘细节(salt and pepper noise filter and weighted)

Image feature extraccting using sift

：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)