JalaliLabUCLA / Jalali-Lab-Implementation-of-RAISR

Implementation of RAISR (Rapid and Accurate Image Super Resolution) algorithm in Python 3.x by Jalali Laboratory at UCLA. The implementation presented here achieved performance results that are comparable to that presented in Google's research paper (with less than ± 0.1 dB in PSNR). Just-in-time (JIT) compilation employing JIT numba is used to speed up the Python code. A very parallelized Python code employing multi-processing capabilities is used to speed up the testing process. The code has been tested on GNU/Linux and Mac OS X 10.13.2 platforms.

JalaliLabUCLA
JalaliLabUCLA
Date Created 2018-07-29 (5 years ago)
Commits 23 (last one 5 years ago)
Stargazers 127 (0 this week)
Watchers 7 (0 this week)
Forks 47
License gpl-3.0
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RepositoryStats indexes 534,880 repositories, of these JalaliLabUCLA/Jalali-Lab-Implementation-of-RAISR is ranked #231,526 (57th percentile) for total stargazers, and #259,002 for total watchers. Github reports the primary language for this repository as Python, for repositories using this language it is ranked #41,303/103,597.

JalaliLabUCLA/Jalali-Lab-Implementation-of-RAISR is also tagged with popular topics, for these it's ranked: python (#10,520/20457),  image-processing (#514/1008),  super-resolution (#155/299)

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JalaliLabUCLA/Jalali-Lab-Implementation-of-RAISR has 3 open pull requests on Github, 0 pull requests have been merged over the lifetime of the repository.

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updated: 2024-03-15 @ 05:45am, id: 142743983 / R_kgDOCIIZrw