https://github.com/tecnickcom/inedi
iNEDI (improved New Edge-Directed Interpolation) Image Zooming Algorithm
https://github.com/tecnickcom/inedi
Last synced: 6 months ago
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iNEDI (improved New Edge-Directed Interpolation) Image Zooming Algorithm
- Host: GitHub
- URL: https://github.com/tecnickcom/inedi
- Owner: tecnickcom
- License: other
- Created: 2016-06-29T15:02:41.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2020-02-01T10:45:43.000Z (over 5 years ago)
- Last Synced: 2025-04-02T22:51:14.955Z (6 months ago)
- Language: MATLAB
- Size: 34.2 KB
- Stars: 28
- Watchers: 3
- Forks: 9
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
- License: LICENSE
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README
# iNEDI
*iNEDI (improved New Edge-Directed Interpolation) Image Zooming Algorithm*
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*Please consider supporting this project by making a donation via [PayPal](https://www.paypal.com/cgi-bin/webscr?cmd=_donations¤cy_code=GBP&business=paypal@tecnick.com&item_name=donation%20for%20inedi%20project)*
* **category** Application
* **package** \Com\Tecnick\inedi
* **author** Nicola Asuni
* **copyright** 2006-2016 Nicola Asuni - Tecnick.com LTD
* **license** http://www.gnu.org/copyleft/lesser.html GNU-LGPL v3 (see LICENSE.TXT)
* **link** https://github.com/tecnickcom/inedi
* **version** 1.6.2
## Description
This projects contains a Matlab implementation of the iNEDI (improved New Edge-Directed Interpolation) algorithm to enlarge (zoom) digital images.
This inedi.m function returns an enlarged image by a factor of 2^ZK for both horizontal and vertical directions.
This function implements the technicque described in:
N. Asuni, "iNEDI - Tecnica non lineare per l'interpolazione di immagini," Master's thesis - University of Cagliari, 2007.
Thesis [ITA]: http://www.tecnick.com/pagefiles/appunti/iNEDI_tesi_Nicola_Asuni.pdf
Presentation [ITA]: http://www.tecnick.com/pagefiles/appunti/iNEDI_presentazione_Nicola_Asuni.pdf
## USAGE
-
[EIM] = inedi(IM)
[EIM] = inedi(IM, ZK)
[EIM] = inedi(IM, ZK, MT)
[EIM] = inedi(IM, ZK, MT, ML)
[EIM] = inedi(IM, ZK, MT, ML, BT)
[EIM] = inedi(IM, ZK, MT, ML, BT, BS)
[EIM] = inedi(IM, ZK, MT, ML, BT, BS, SZ)
[EIM] = inedi(IM, ZK, MT, ML, BT, BS, SZ, VR)
## INPUT
IM : source image
ZK : power of the zoom factor (default = 1)
the image enlargement on vertical and horizontal direction is
2^ZK; the final image size will be (SIZE * 2^ZK) - (2^ZK - 1)
MT : maximum radius of the local circular window (default = 9)
ML : minimum radius of the local circular window (default = 3)
BT : brightness tollerance (default = 32)
Y points are choosen from the ones inside a circular area around
the pixel to be interpolated. These pixels must have a
brightness between a range defined by
the minimum and maximum brightness values of the 4 neighbors
pixels of the pixel to interpolate. This range is extended by
+/- BT value.
BS : maximum brigthess difference for smooth areas (default = 4)
This parameter is compared to the difference between the maximum
and minimum brightness value of 4 neighbors pixels to
discriminate between smooth areas (bicubic interpolation) and
edge areas (iNEDI interpolation).
SZ : number of image bits per layer (default = 8)
VR : verbose mode (default = false)
if true prints some information during calculation
## OUTPUT
EIM : enlarged image
## Examples
Please check the inediexample.m file on how to use this function.
## Notes
This implementation is not intended to be used in a production environment. The main purpose of this script is to clearly show how this technique works. Better performaces could be obtained using a compiled version or rewriting this technique using a low-level programming language.
## KEYWORDS
iNEDI, NEDI, image, zooming, magnification, upsizing, resampling, resolution enhancement, interpolation, super-resolution, covariance-based adaptation, geometric regularity, matlab, octave.