huofuman

用delaunay三角剖分和网格填充对离散点云数据进行网格重建(Mesh reconstruction of discrete point cloud data using Delaunay triangulation and mesh filling)

说明：  RGB-IHS变换：图像进行 RGB-HIS 正变换，分别对明度、饱和度、色调进行线性 拉伸显示；然后再进行反变换 (RGB-IHS transformation: the image is RGB-HIS transformation, respectively, lightness, saturation, hue, a linear stretch display then the inverse transform)

基于暗通道先验理论的去雾算法，使用rgb暗通道计算大气光及透射率获得去雾图像(Since the scene radiance is usually not as bright as the atmospheric light, the image after haze removal looks dim. So we increase the exposure of J(x) for display.)

一种简单的代数重建算法，用于CT图像二维重建，供初学者学习使用。(A simple algebraic reconstruction algorithm, used in CT image reconstruction, for beginners learning to use.)

此程序采用 FCM，模糊c 均值方法，用于边缘检测(This program uses FCM, fuzzy C mean method, for edge detection)

能针对二值图像进行曲线的提取. 对于背景不太复杂的图像，效果可以。 只针对单像素(extract curve from binary image only for single pixel line.)

C# WPF 图片局部放大镜 示例源码

SIFT，即尺度不变特征变换（Scale-invariant feature transform，SIFT），是用于图像处理领域的一种描述。这种描述具有尺度不变性，可在图像中检测出关键点，是一种局部特征描述子。 该方法于 1999 年由 David Lowe 首先发表于计算机视觉国际会议（International Conference on Computer Vision，ICCV），2004 年再次经 David Lowe 整理完善后发表于 International journal of computer vision（IJCV） 。截止 2014 年 8 月，该论文单篇被引次数达 25000 余次。(来自百度)(SIFT, namely Scale-invariant feature transform (SIFT), is a description used in the field of image processing. This description has scale invariance and can detect key points in images. It is a local feature descriptor. This method was first published by David Lowe at the International Conference on Computer Vision (ICCV) in 1999 and published in the International Journal of Computer Vision (IJCV) in 2004 after it was sorted out and perfected by David Lowe again. As of August 2014, more than 25,000 citations have been cited. (From Baidu))

相位编组算法实现纹理边缘的直线检测.用于快速直线提取(Phase Group texture edge detection algorithm to achieve a straight line. For fast line extraction)

用于脸部识别时，使用基于像素和区域的图像特征核的稀疏表示的识别算法。(When used in face recognition using image recognition algorithm based on feature pixel and regional nuclear sparse representation.)