亚像素图像处理

This package is a MATLAB implementation of our paper Eulerian Video Magnification for Revealing Subtle Changes in the World ACM Transaction on Graphics, Volume 31, Number 4 (Proceedings SIGGRAPH 2012) The paper and example videos can be found on the project web page http://people.csail.mit.edu/mrub/vidmag/ The code is supplied for educational purposes only. Please refer to the enclosed LICENSE.pdf file regarding permission to use the software. Please cite our paper if you use any part of the code or data on the project web page. Please contact the authors below if you wish to use the code commercially. The code includes the following combination of spatial and temporal filters, which we used to generate all the results in the paper: Spatial Temporal ========================================================================= Laplacian pyramid Ideal bandpass Laplacian pyramid Butterworth bandpass Laplacian pyramid Second-order IIR bandpass Gaussian pyramid Ideal bandpass The code was written in MATLAB R2011b, and tested on Windows 7, Mac OSX and Linux. It uses the pyramid toolbox by Eero Simoncelli (matlabPyrTools), available at http://www.cns.nyu.edu/~eero/software.php. For convenience, we have included a copy of version 1.4 (updated Dec. 2009) of their toolbox here. The code currently also requires MATLAB's Image Processing Toolbox. We hope to remove this dependency in the future. To reproduce the results shown in the paper: 1) Download the source videos from the project web page into a directory "data" inside the directory containing this code. 2) Start up MATLAB and change directory to the location of this code. 3) (Optional) Run "make.m" to build pyramid toolbox libraries (this is REQUIRED if using Mac OS and MATLAB newer than 2011b). 4) Run "install.m". 5) Run "reproduceResults.m" to reproduce all the results in the paper. See the "reproduceResults.m" script for more details. NOTE: Generating each of the results will take a few minutes. We have selected parameters that result in better looking videos, however, depending on your application, you may not need such high quality results. The parameters we used to generate the results presented in the paper can be found in the script "reproduceResults.m". Please refer to the paper for more detail on selecting the values for the parameters. In some cases, the parameters reported in the paper do not exactly match the ones in the script, as we have refined our parameters through experimentation. Feel free to experiment on your own! For questions/feedback/bugs, or if you would like to make commercial use of this software, please contact Hao-Yu Wu <haoyu@mit.edu> or Michael Rubinstein <mrub@mit.edu> Computer Science and Artificial Intelligence Lab, Massachusetts Institute of Technology Sep 10, 2012