simple-camera-pipeline

Version 1.0.0 (69 MB) by Abdelrahman Kamel

A simple and light-weight camera image processing pipeline

https://github.com/AbdoKamel/simple-camera-pipeline

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Updated 28 Jul 2022

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A simple and light-weight camera image processing pipeline implemented in MATLAB.

Start by running DEMO.m

This is the code used to render the sRGB images from the Raw-RGB images of the Smartphone Image Denoising Dataset (SIDD)
https://www.eecs.yorku.ca/~kamel/sidd/

This code is helpful for participants of the real image denoising challenges on CodaLab:

NTIRE 2019 Real Image Denoising Challenge - Track 1: Raw-RGB
https://competitions.codalab.org/competitions/21258

NTIRE 2019 Real Image Denoising Challenge - Track 2: sRGB
https://competitions.codalab.org/competitions/21266

Enjoy!

Cite As

Abdelhamed, Abdelrahman, et al. “A High-Quality Denoising Dataset for Smartphone Cameras.” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018, doi:10.1109/cvpr.2018.00182.

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MATLAB Release Compatibility

Created with R2017a

Compatible with any release

Platform Compatibility

Windows macOS Linux

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Version	Published	Release Notes
1.0.0	28 Jul 2022

To view or report issues in this GitHub add-on, visit the GitHub Repository.

MLA	Abdelhamed, Abdelrahman, et al. “A High-Quality Denoising Dataset for Smartphone Cameras.” 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2018, doi:10.1109/cvpr.2018.00182.
APA	Abdelhamed, A., Lin, S., & Brown, M. S. (2018). A High-Quality Denoising Dataset for Smartphone Cameras. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE. Retrieved from https://doi.org/10.1109%2Fcvpr.2018.00182
BibTeX	@inproceedings{Abdelhamed_2018, doi = {10.1109/cvpr.2018.00182}, url = {https://doi.org/10.1109%2Fcvpr.2018.00182}, year = 2018, month = {jun}, publisher = {{IEEE}}, author = {Abdelrahman Abdelhamed and Stephen Lin and Michael S. Brown}, title = {A High-Quality Denoising Dataset for Smartphone Cameras}, booktitle = {2018 {IEEE}/{CVF} Conference on Computer Vision and Pattern Recognition} }