mask-code

说明：  基于matlab上的菲涅耳离轴全息记录与再现程序，能对图像进行相应处理得到其全息图。同时能将其再现还原。(Based on the Fresnel off-axis holographic recording and reconstruction program on MATLAB, the hologram of the image can be obtained by corresponding processing. At the same time, it can be reproduced and restored.)

Pacote com icones do Help do Windows

【实例简介】

C# 浏览大图片 例子源码

斯坦福大学的姚邦鹏开发的一个图像分类算法，使用random forest实现了图像的精细区域描述，赢得了PASCAL VOC2011图像分类竞赛中的winner prize.经测试，程序完全可运行，且提供了MAC和Windows下的两种程序。(Image Classification: An Integration of Randomization and Discrimination in A Dense Feature Representation The goal of our method is to identify the discriminative fine-grained image region that distinguishes different classes. To achieve this goal we sample image regions from dense sampling space and use a random forest algorithm with discriminative classifier. Each node of the tree of random forest is trained and tested with fine-grained image patches combining the information from upstream nodes together. We implemented each node of the tree with a discriminative SVM classifier, which makes the node as a strong classifier. )

基于脆弱性的水印嵌入算法，包括水印嵌入，水印攻击等(Based on the vulnerability of the watermark embedding algorithm, including watermark embedding, watermark attacks and so on)

离散分数阶傅立叶变换，算法参考 C. Candan, M.A. Kutay, and H.M. Ozaktas. The discrete Fractional Fourier Transform. IEEE Trans. Sig. Proc., 48:1329--1337, 2000 (Discrete fractional Fourier transform algorithm reference C. Candan, MA Kutay, and HM Ozaktas. The discrete Fractional Fourier Transform. IEEE Trans. Sig. Proc., 48:1329- 1337, 2000)

多尺度快速角点检测算法（FAST).Adaptive and generic corner detection based on the accelerated segment test. 出处 Computer Vision–ECCV 2010(Multi-scale fast corner detection algorithm (FAST) Adaptive and generic corner detection based on the accelerated segment test. Computer Vision-ECCV 2010)

sar 图像边缘检测算子，代码简洁，能够运行成功。(sar image edge detection，it s simple and useful 。)

改程序就代码可以找出从不同角度或区间的两幅遥感影像的同名点(Change the program code can find it from different angles of the same name point or interval of two remote sensing images)