Can web-based image processing and visualization tools easily integrate into existing websites without significant time and effort? Our Boostlet.js library addresses this challenge by providing an open-source, JavaScript-based web framework to enable additional image processing functionalities. Boostlet examples include kernel filtering, image captioning, data visualization, segmentation, and web-optimized machine-learning models. To achieve this, Boostlet.js uses a browser bookmark to inject a user-friendly plugin selection tool called PowerBoost into any host website. Boostlet also provides on-site access to a standard API independent of any visualization framework for pixel data and scene manipulation. Web-based Boostlets provide a modular architecture and client-side processing capabilities to apply advanced image-processing techniques using consumer-level hardware. The code is open-source and available.
@article{arxiv.2405.07868,
title = {Boostlet.js: Image processing plugins for the web via JavaScript injection},
author = {Edward Gaibor and Shruti Varade and Rohini Deshmukh and Tim Meyer and Mahsa Geshvadi and SangHyuk Kim and Vidhya Sree Narayanappa and Daniel Haehn},
journal= {arXiv preprint arXiv:2405.07868},
year = {2024}
}