HVS_DWT_new

说明：  本程序使用MFC编写了一个能够在同一界面上显示立体图形的三视图的源程序。(This program using MFC wrote a can in the same interface shown on the SanShiTu three-dimensional graph of the source program.)

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)

tsne 快速降维算法 效果好于PCA 算法(tsne fast dimensionality reduction algorithm is better than PCA algorithm)

对植物图像进行图像分割，区域标记，区域提取(Images of plant image segmentation, region markers, regional extraction)

傅立叶变换，等距离采样，等角度采样，轮廓提取，形态处理(Fourier transform, equidistant sampling, in terms of sampling, contour extraction, morphological processing)

C++Builder编写的图象处理程序(带示例)(C++ Builder prepared image processing procedures (with examples))

主要是关于模糊熵的，里面还和灰色关联度有点联系。搞图像的应该可以看的懂的。(Mainly on fuzzy entropy, which has little contact and the gray. Should be able to read out the image of understand.)

局部二进制模式，LBP，是已被用于纹理特征的一个 分类。在本文中，提出了一种基于使用这些功能的方法 检测缺陷图案的面料。在培训阶段，在第一个步骤LBP算子是 施加到无缺陷织物样品，逐个象素和参考的所有的行（列） 特征矢量的计算。那么这个图像被分为Windows和LBP算子是 应用这些窗口的每一行（列）。根据与参考比较 特征向量一个合适的阈值，无缺陷的窗户被发现。在检测阶段中，一个 测试图像被划分成的窗户，并使用阈值时，有缺陷的窗口可以 检测到。该方法简单，灰度不变。由于其简单性， 线上实现是可能的。(Local Binary Patterns, LBP, is one of the features which has been used for texture classification. In this paper, a method based on using these features is proposed for detecting defects in patterned fabrics. In the training stage, at first step LBP operator is applied to all rows (columns) of a defect free fabric sample, pixel by pixel, and the reference feature vector is computed. Then this image is divided into windows and LBP operator is applied to each row (column) of these windows. Based on comparison with the reference feature vector a suitable threshold for defect free windows is found. In the detection stage, a test image is divided into windows and using the threshold, defective windows can be detected. The proposed method is simple and gray scale invariant. Because of its simplicity, online implementation is possible as well. )

光谱角(Spectral Angle)衡量像素间的相关性存在着差异，本程序用于计算光谱角，及光谱角匹配(Spectral Angle (Spectral Angle) to measure the correlation between pixels there are differences, the process used to calculate the spectral angle, and spectral angle matching)

说明：  利用小波包分解对一个二维含躁图像进行去噪处理(Using Wavelet Packet Decomposition to Denoise a Two-Dimensional Fidgety Image)