A Novel Framework for Interactive Visualization and Analysis of Hyperspectral Image Data

Abstract

Multispectral and hyperspectral images are well established in various fields of application like remote sensing, astronomy, and microscopic spectroscopy. In recent years, the availability of new sensor designs, more powerful processors, and high-capacity storage further opened this imaging modality to a wider array of applications like medical diagnosis, agriculture, and cultural heritage. This necessitates new tools that allow general analysis of the image data and are intuitive to users who are new to hyperspectral imaging. We introduce a novel framework that bundles new interactive visualization techniques with powerful algorithms and is accessible through an efficient and intuitive graphical user interface. We visualize the spectral distribution of an image via parallel coordinates with a strong link to traditional visualization techniques, enabling new paradigms in hyperspectral image analysis that focus on interactive raw data exploration. We combine novel methods for supervised segmentation, global clustering, and nonlinear false-color coding to assist in the visual inspection. Our framework coined Gerbil is open source and highly modular, building on established methods and being easily extensible for application-specific needs. It satisfies the need for a general, consistent software framework that tightly integrates analysis algorithms with an intuitive, modern interface to the raw image data and algorithmic results. Gerbil finds its worldwide use in academia and industry alike with several thousand downloads originating from 45 countries.

Hyperspectral Panoramic Imaging

“…The interactive visualisation and analysis framework for multiand hyperspectral data Gerbil (Jordan et al, 2016) is an Open-Source software which implements, among other things, some false-colouring algorithms which map the spectral information to RGB values using dimensionality reduction. Figure 13 shows the result of false-coloring using a self-organizing map (SOM) as described in (Jordan and Angelopoulou, 2013).…”

Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping

“…A reflectance standard must be placed within the acquired scene in order to normalize the reflectance measurements. The resulting hypercubes were finally analyzed here using MATLAB ® , Python, and Gerbil [19].…”

IDCube Lite: Free Interactive Discovery Cube software for multi and hyperspectral applications

“…Well-known software packages, such as ENVI, 12 are comprehensive; however, they are mostly used for remote sensing applications. A handful of free hyperspectral software packages with strong innovative algorithms (e.g., Gerbil 13 or MultiSpec 14 ) are more suitable for experts and are limited to geospatial applications. Introduced in 2020, the Hyperspectral Toolbox from MATLAB 15 has very few algorithms, is limited in the number of supported file formats and is largely command-line based.…”