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陆吾生教授是加拿大维多利亚大学电气与计算机工程系的教授。此课件为其在国内大学短期精品课程的课件。包含最优化问题求解,压缩感知方法及其在稀疏信号和图像处理中的应用(压缩、重构、降噪等)。-Professor Lu Wusheng University of Victoria, Canada Professor of Electrical and Computer Engineering. The courseware for the University in the domestic short
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基于窗口稀疏点匹配以及三维重建,包括了示例图片以及执行文件-Sparse points matching based on window and reconstruction, including a sample image and perform file
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spgl1的最新版本1.7,用于图像处理中的大规模稀疏重建。-spgl1 the latest version 1.7, for image processing of large-scale sparse reconstruction.
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集束调整是指同时调整相机参数和物点坐标,使重投影误差取得最小值的优化过程,可用于三维重建-sba, a C/C++ package for generic sparse bundle adjustment is almost invariably used as the last step of every feature-based multiple view reconstruction vision algorithm to obtain optimal 3D structure and
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本源码是关于未校正图像的稀疏点匹配与重建的代码,其中还包括了用于实验的图像-The source is sparse on the uncorrected image point matching and reconstruction code, which also includes images used in experiments
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Bundler是一个采用C和C++开发的称为sfm(struct-from-motion)的系统,它能够利用无序的图片集合(例如来自网络的图片)重建出3D的模型。最早的版本被用在Photo Tourism的项目上。
Bundler的输入是一些图像、图像特征以及图像匹配信息,输出则是一个根据这些图像反应的场景的3D重建模型,伴有少量识别得到的相机以及场景几何信息。系统借用一个由Lourakis 和Argyros提供的称为Sparse Bundle Adjustment的开发包的修改版
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利用稀疏矩阵思想进行图像的超分辨率重建,效果较好。-Thinking of using sparse matrix for image super-resolution reconstruction, the effect is better.
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读取二值图像,转化为稀疏信号,变换到压缩域,然后用压缩感知进行重构。-Read binary image, into sparse signal, transform to the compressed domain, and then use compressed perception reconstruction
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完成两幅图像的稀疏点的匹配和重建,C++的编程环境,opencv函数库-Do two sparse points matching and reconstruction of the image, c++ programming environment, opencv function library
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此程序,是应用在压缩感知方面的稀疏表示,图像重构。程序中利用现在流行的CS理论,在采样率为0.9时,成功的实现了图像重构-This procedure is used in the compressed sensing aspects of sparse representation, image reconstruction. Program using the now popular CS theory, the sampling rate is 0.9, the successful re
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图像超分辨率重建算法,通过稀疏混合估计来实现,效果不错。-Image super-resolution reconstruction algorithm, by mixing estimates sparse achieved good results.
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小波稀疏分解和重构算法,适合通信信号和图像重构-Sparse wavelet decomposition and reconstruction algorithm for communications signal and image reconstruction
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这段代码利用的工具包SPAMS,该文件是实现图像的稀疏表示,图像的重建以及其重建的质量评价等等。-Use this code toolkit SPAMS, the file is a sparse representation of image, image reconstruction and rebuilding of its quality assessment and so on.
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可压缩传感,随机投影,稀疏性,非相干,图像重建-Compressible sensing, random projection, sparse, non-coherent, image reconstruction
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稀疏重建与压缩感知代码,是有关于图像重构的源代码,对lena图像进行重构-Sparse Reconstruction and compressed sensing code, is the source code on image reconstruction, image reconstruction for lena
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基于稀疏表示的超分辨率图像重建硕士论文,一共六篇,比较全面的介绍了基于稀疏表示的超分辨重建的方法以及详细的实现步骤,是比较好的入门资料-the master s thesis of Super-resolution image reconstruction based on sparse coding , a total of six, a more comprehensive descr iption of the super-resolution reconstruction method
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通过各种方法对图像进行稀疏化分解,最后用压缩感知算法进行重建(The image is sparse decomposed by various methods, and finally reconstructed by compressed sensing algorithm)
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利用稀疏表示原理来进行单幅影像超分辨重建(use sparse representation to single image super resolution)
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压缩感知稀疏度自适应重构算法,含有子功能程序和主程序,注意程序中数值与所选图像尺寸的匹配(Compressed sensing sparse adaptive reconstruction algorithm, contains subfunction program and main program, notice the value of the program matching the selected image size.)
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该文包含了压缩感知图像重构算法,有omp,cosamp,sp,可以选择观测矩阵高斯随机矩阵,稀疏随机矩阵,部分哈达码矩阵。(This paper includes compressed sensing image reconstruction algorithm. It has OMP, CoSaMP and sp. It can choose observation matrix Gauss random matrix, sparse random matrix and partial Had
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