I-Corps: Interactive Software for Hyperspectral Image Analysis

The broader impact/commercial potential of this I-Corps project is to simplify the workflow, reduce analysis time, and enable deep searching capabilities across hyperspectral datasets using a new computational platform. Hyperspectral imaging, or chemical imaging, is the combination of spectroscopy and digital imaging. The proposed system incorporates advanced imaging and machine learning algorithms to streamline data processing and enable users to focus on the application itself, rather than spending time and money on developing image processing algorithms.

Hyperspectral imaging is broadly used to diagnose diseases and measure a patient's response to therapy, to enhance product quality by enabling optical sorters to identify and remove defective products, and to identify minerals from drill cores and remote sensing. A potential early application for the software platform will be in agriculture to identify early stress in crops, assess soil health, quantify water resources, and predict harvest yields.

This I-Corps project further develops a software platform for deep mining of data derived from hyperspectral imaging. The system performs several essential operations in the spectral imaging domain and enables advanced image analysis for users across a range of technical proficiencies. The strength of the proposed software lies in its intuitive design that enables the user to perform high level data analysis from image processing to machine learning via a visual, interactive interface.

Built around a collection of current and proprietary spectral imaging algorithms, the software facilitates the search of hidden information inside large datasets, providing broad improvements in data analysis. The package can be operated without prior programming skills and allows most currently used data formats to be processed in real time. The interactivity, object identification, and machine learning algorithms enable high efficiency during analysis of hyperspectral images.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.