chubu

5相位编组法实现纹理直线边缘的检测matlab程序代码。不同于hough变换。附带文字的原理讲解(The five-phase grouping texture straight edge detection ，matlab code. Different from the hough transform. explain with the accompanying text )

一些dwt数字水印 源码和一些资料希望对大家有用 呵呵(dwt digital watermarking)

基于非局部图像去噪模型的遥感图像融合的变分方法。该变分方法采用梯度下降法。(Variational method of remote sensing images nonlocal image denoising model fusion. The variational method using gradient descent.)

这是一篇讲述最新的干涉图处理的关键技术的文章，非常实用！(This is an article about the latest key interferogram processing technology is very useful!)

背景音乐只是随便写了写,具体的可以改数组里的数字.有点闪的效果还是不太好看. (Background music just casually write write array of specific numbers can be changed. Bit flash effect is still quite nice.)

二值图像的Zhang快速并行细化算法，具有速度快、保持细化后曲线的连通性和无毛刺产生等优点。(Zhang fast parallel thinning algorithm)

使用camshift方法进行运动目标跟踪，（修改了网上原有的camshift算法里的一些bug）(moving object tracking by camshift method,(modification edition of the original code on the web))

累加颜色直方图法图像检索,包含基本程序、图片库以及WORD说明文档(Cumulative color histogram image retrieval, including basic procedures, photo gallery and documentation WORD)

说明：  对指定的一幅含有多个目标的灰度图像，进行基于阈值的图像分割处理，对结果图像进行基于数学形态学的后处理设计，以得到更理想的目标区域。最后对结果图像进行区域标记（以颜色区分不同区域）并提取目标个数、各目标区域的面积、圆形度等特征。(The gray image with multiple targets is segmented based on threshold, and the result image is designed based on mathematical morphology to get a better target area. Finally, we mark the region of the result image (distinguish different regions by color) and extract the number of targets, the area of each target region, roundness and other features.)

视网膜血管检测的Gabor变换和机器学习，教程 本教程将演示如何Gabor变换和广义 的线性模型（GLM）可用于视网膜血管检测 图像。 ，我们将尝试检测视网膜血管从 的训练图像，首先，Gabor滤波器与图像卷积。 GLM将使用Gabor变换的图像特征确定 （独立变量）和容器的位置 为结果（因变量）。( Retinal Vessel Detection by Gabor Transform and Machine Learning, a Tutorial This tutorial will demonstrate how Gabor transforms and generalized linear model (GLM) can be used for detection of retinal vessels in images. Specifically, we will attempt to detect the retinal vessels a training image , by first, convoluting multiple Gabor filters with the image. A GLM will be determined using the Gabor transformed images as features (the independent variables), and the locations of the vessels as the outcome (the dependent variable).)