# CNN-POCS

**Repository Path**: sevenysw/CNN-POCS

## Basic Information

- **Project Name**: CNN-POCS
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 1
- **Forks**: 0
- **Created**: 2020-04-19
- **Last Updated**: 2024-06-20

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# CNN-POCS
 CNN-POCS algorithm for seismic data interpolation.

 This repository contains the reproducible code for the article ["Can learning from image denoising be used for seismic data interpolation?"](https://library.seg.org/doi/10.1190/geo2019-0243.1)  This article can also be reached at [Arxiv](https://arxiv.org/pdf/1902.10379.pdf) but it is somehow out of date.

## Requirements and Dependencies
This repository depends on Matlab and matconvnet. Matlab beyond 2018a and [matconvnet](https://www.vlfeat.org/matconvnet/) 1.0beta25 are recommended. CUDA is required for training process/gpu testing. Please refer to [Matlab GPU support](https://www.mathworks.com/help/parallel-computing/gpu-support-by-release.html) to setup your environment.
## CNN-POCS workflow
<img src="figs/flowchart.png">

## Training
The training code can be found in [TrainingCodes](https://github.com/AlbertZhangHIT/CNN-POCS/tree/master/TrainingCodes).

## Seismic data interpolation & denoising
We provide few demos for reproducing some results. The pre-trained models using natural images are in folder [models](https://github.com/AlbertZhangHIT/CNN-POCS/tree/master/models). The hyperbolic events data and the synthetic 3D data are included in [seismicData](https://github.com/AlbertZhangHIT/CNN-POCS/tree/master/seismicData).

1. [Demo\_pocs\_cnn.m](https://github.com/AlbertZhangHIT/CNN-POCS/tree/master/Demo_pocs_cnn.m) is provided for testing the CNN-POCS algorithm for seismic data interpolation.
2. [Demo_cnndenoise.m](https://github.com/AlbertZhangHIT/CNN-POCS/tree/master/Demo_cnndenoise.m) is provided for testing denoising 2D seismic data using natural images pretrained CNN models.
3. [Demo_cnndenoise3D.m](https://github.com/AlbertZhangHIT/CNN-POCS/tree/master/Demo_cnndenoise3D.m) is provided for testing denoising 3D seismic data.

# Citation
If this repository helps you with your research, please consider citing our work

	
	@article{zhang2020can,
	  title={Can learning from natural image denoising be used for seismic data interpolation?},
	  author={Zhang, Hao and Yang, Xiuyan and Ma, Jianwei},
	  journal={Geophysics},
	  volume={85},
	  number={4},
	  pages={1--142},
	  year={2020},
	  publisher={Society of Exploration Geophysicists}
	}