Coltransfer

sift特征点检测及图像拼接，matlab7.0实现的，我从别人那里整过来的，测试的话，用在matlab里面直接调用match( b1.jpg , b2.jpg )即可，我测试成功，里面也有说明文档，为了科研，共享，希望大家有好的代码都0分共享，与己方便，与人方便，中国科研才会发展更迅速(sift feature point detection and image stitching of, matlab7.0 realized, I come from others where the whole test, used in matlab inside direct calls to match (' b1.jpg' , ' b2.jpg' ) can I test success, which also has documentation, in order to research, share, and hope everyone has a good code sharing, and has convenient, and accommodating, the more rapid development of China' s scientific research will)

处理Gamma乘性噪声的PPB方法，考虑了非局部patch的相似性，可处理SAR图像去噪。(The PPB method for multicative noise removal, which based on the Probabilistic Patch similarity.)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)

简单的图形文字识别软件，希望大家喜欢我的分享，谢谢(Simple graphical text recognition software, I hope you like my share, thank you)

jpeg无失真压缩源代码(jpeg lossless compression source code)

这是一段视频分割的源代码 效果比较好 希望对大家有帮助(This is a video segmentation of the source code for the effect we hope to help)

利用棋盘格对相机进行标定，加入误差判定及像素空间到实际物理空间的距离计算(The camera is calibrated by checkerboard, the error is added and the distance of pixel space to the actual physical space is calculated)

打开24位彩色bmp文件, 显示该图像 将图像内容顺时针旋转90度后显示出来 将图像分成等大小的4块，将第1和第3块像素互换后保存 将旋转后的图像转换成灰度图像显示，并保存 对灰度图像求Sobel边缘图，显示出来，并保存 对灰度图像进行Gaussian平滑，并保存（需要体会平滑的作用） 对灰度图像进行2值化(Open 24-bit color bmp files, displays the image will rotate clockwise image content displayed image is divided into four equal-sized 90 degrees, the first and three pixels after swap to save the rotated image conversion ashes of the image display, and save images to grayscale seeking Sobel edge map is displayed, and save the gray image Gaussian smoothing, and save (experience required smoothing effect) grayscale image binarized)

画图源程序-图像数据显示，可以对数据进行时间轴的曲线显示，也可以是空间轴的多维显示 (Paint source- the image data, the data can be curve shows the time axis, it can be multi-dimensional display space axis)

图像拼接源码实现，包括多频率图像融合，sift特征点配准算法(Image Stitching source implementation, including multi-frequency image fusion, sift feature points matching algorithm)