# imagefusion_noisy_lrr
**Repository Path**: hli1221/imagefusion_noisy_lrr
## Basic Information
- **Project Name**: imagefusion_noisy_lrr
- **Description**: multi-focus image fusion using low-rank representation
- **Primary Language**: Matlab
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No
## Statistics
- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-05-01
- **Last Updated**: 2022-05-01
## Categories & Tags
**Categories**: Uncategorized
**Tags**: image-fusion, low-rank
## README
# Multi-focus Noisy Image Fusion using Low-Rank Representation
[arXiv](https://arxiv.org/abs/1804.09325)
## The framework for fusion method
### DWT for level 2

### NSCT for level 2

### The framework

### Fusion high frequency

### Original images

### Noise images with multi-focus

## Figures
1 original_images
2 mf_noise_images ---- multi-focus images contain different noises
3 focus_images ---- sources images
## Source code
1 main.m --- test demo.
2 'methods' - multi-scale transform frameworks
3 The code of LRR in 'lrr'
solve_lrr.m
solve_l1l2.m
inexact_alm_lrr_l1l2.m, inexact_alm_lrr_l1.m
exact_alm_lrr_l1l2.m, exact_alm_lrr_l1.m
## LRR parts
Thr LRR method is proposed by Guangcan Liu in 2010.
"Liu G, Lin Z, Yu Y. Robust Subspace Segmentation by Low-Rank Representation[C]// International Conference on Machine Learning. DBLP, 2010:663-670."
And we just use this method in our paper without change.
# Citation
For codes:
```
@misc{li2017noisyimagefusion,
author = {Hui Li},
title = {CODE: Multi-focus Noisy Image Fusion using Low-Rank Representation},
year = {2017},
note = {\url{https://github.com/hli1221/imagefusion_noisy_lrr}}
}
```