Convinient class for handling images in JavaScript.
The IPLabImageAccess class has been developed for teaching the coding of Image Processing algorithms at the pixel level. The class is written in JavaScript and is intended to be used in Jupyter Notebooks running the IJavascript kernel. However, it can also be used in a native JavaScript environment. The aim of the IPLabImageAccess class is to facilitate the creation and modification of images in JavaScript and as such it provides an easy-to-use interface to multidimensional arrays which can represent graylevel or color images, offering utility functions and pixel access, while taking care of boundary conditions.
The IPLabImageAccess example notebook.ipynb showcases the basic functionalities of the IPLabImageAccess class. Members of EPFL can use the following link to run the notebook on Noto: https://bit.ly/2FGVRzn
- Creation of new color- or graylevel images from size and initial value parameters or from an existing JavaScript array
- Single-pixel R/W access
- Row/Column R/W access
- Neighborhood R access
- Subimage W access
- Easy access to image size and dimensionality
- Integrated minimum/maximum and normilize methods
- Transpose images
- Compare two images
- Conversion from image to JavaScript array
To use the IPLabImageAccess class, use the require statement. It is recommended to import the class as a constant Image by using the following code
const Image = require('./IPLabImageAccess.js')but it can also be imported as var instead of const to allow for multiple importations.
The class was developed in the most part by:
- Kay Lächler (kay.lachler@epfl.ch, TheUser0571)
under the guidance, help, testing and feedback of:
- Alejandro Noguerón Aramburu (alejandro.nogueronaramburu@epfl.ch, Alejandro-1996)
- Pol del Aguila Pla, (pol.delaguilapla@epfl.ch, poldap)
- Daniel Sage, (daniel.sage@epfl.ch, dasv74)
It was supported by EPFLs Center for Digital Education (CEDE), and it belongs to the Biomedical Imaging Group.
A detailed documentation can be found in the wiki.