https://github.com/motykatomasz/local-laplacian-filters
Reproduction of the paper "Local Laplacian filters: edge-aware image processing with a Laplacian pyramid" for the course Advanced Digital Image Processing at TU Delft
https://github.com/motykatomasz/local-laplacian-filters
edge-aware-processing image-processing laplacian-pyramid opencv python
Last synced: 7 months ago
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Reproduction of the paper "Local Laplacian filters: edge-aware image processing with a Laplacian pyramid" for the course Advanced Digital Image Processing at TU Delft
- Host: GitHub
- URL: https://github.com/motykatomasz/local-laplacian-filters
- Owner: motykatomasz
- Created: 2021-05-01T10:28:35.000Z (over 4 years ago)
- Default Branch: main
- Last Pushed: 2021-10-08T12:03:49.000Z (about 4 years ago)
- Last Synced: 2025-03-17T08:13:46.334Z (7 months ago)
- Topics: edge-aware-processing, image-processing, laplacian-pyramid, opencv, python
- Language: Python
- Homepage:
- Size: 16.9 MB
- Stars: 16
- Watchers: 2
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Local-Laplacian-Filters
Reproduction of the paper "Local Laplacian filters: edge-aware image processing with a Laplacian pyramid" for the course Advanced Digital Image Processing at TU Delft
## How to run the algorithm?
### Requirements:
* NumPy
* OpenCV
* PIL
* SharredArray
### Options:
* img_path: path to the input image
* out_path: path to save the results
* color_img: Indicates whether we process color or grayscale image.
* intensity_img: Whether to use intensity image for processing color image
* mapping_func: Type of remapping function 'color' or 'grayscale'
* levels: Number of levels for Gaussian/Laplacian Pyramid
* sigma: Algorithm Hyperparameter
* alpha: Algorithm Hyperparameter
* beta: Algorithm Hyperparameter
* num_processes: Number of processes to run the algorithm
### Example Usage:
> *python main.py --img_path data/desk_256.hdr --out_path results/result.png --color_img True --intensity_img True --mapping_func grayscale
--levels 5 --sigma 0.4 --alpha 1.0 --beta 0.5 --num_processes 16*
### Exemplary results (Detail manipulation):
