ISIS - Intelligent Searching of Images and Signals

The Los Alamos ISIS program is developing a set of software packages and reconfigurable computing hardware to enable rapid exploration and analysis of images and signals. Packages in the ISIS software suite build customized, robust, automated algorithms for feature extraction and analysis. With current sensor platforms collecting a flood of high-quality data, automatic feature extraction (AFE) has become a key to enabling human analysts to keep up with the flow. The ISIS software packages produce AFE tools for features in multispectral, hyperspectral, panchromatic, and multi-instrument fused imagery. Both spectral and spatial signatures of image features are discovered and exploited. The software features an interactive graphical user interface, and a parallel/scalable processing backend that runs on off-the-shelf computers (Linux and Solaris workstations; the POOKA package runs on Windows workstations with the addition of a commercial off-the-shelf reconfigurable computing board).

ISIS tools have been applied to a number of real word applications (see Figure above), including urban disasters (New York City, Sep 11), natural disasters (Cerro Grande/Los Alamos wildfire), biomedical imagery (cancer and pathogen detection), and space exploration (Mars and beyond).

The Los Almaos ISIS software suite is a program of the Los Alamos National Laboratory's Nonproliferation and International Security (NIS) Division.

Background
Extraction of features from large and possibly multi-instrument imagery data sets is a crucial task facing many communities of researchers and analysts. With new distribution technologies and data formats making storage and dissemination of huge amounts of data cheaper and easier, the bottle-neck to successful exploitation of this flood of raw information rests on the availability of analysis tools. From change detection for broad-area environmental monitoring, to terrain catergorization for cartographers, development of image-processing tools for novel datasets is an expensive business, often requiring a significant investment of time by highly skilled scientists, analysts, and programmers. With the arrival of multi-spectral sensors platforms such as Landsat and high-resolution imaging sysensors such as IKONOS and Quickbird, the analyst can now search for spectral, spatial, and possibly hybrid spatio-spectral signatures, requiring development of whole new tool-kits. Our own work in the field of remote sensing science has led us to seek easy-to-use, accelerated tool-makers. Since creating and developing customized algorithms is so important and yet so expensive, we have begun investigating machine learning approaches to this problem.

Los Alamos ISIS Software Suite
The Los Alamos ISIS software suite currently includes four "tool-maker" image/signal processing packages, as well as a common point-and-click graphical user interface (called Aladdin) for providing training data and running the tool-makers. The four tool-maker packages are:

GENIE uses techniques from genetic programming to build customized spatio-spectral algorithms for a wide range of sensors (electro-optical, infrared, and other modalities; panchromatic through hyperspectral data). GENIE is designed to process imagery, and has also been applied to image-like signals (e.g., "waterfall" displays). GENIE was the first toolmaker package developed for the Los Alamos ISIS software suite.

POOKA combines reconfigurable computing hardware with evolutionary algorithms to allow rapid prototyping of image and signal processing algorithms implemented at the chip level. This enables POOKA to rapidly produce customized automated feature extraction algorithms the run hundreds of times faster than equivalent algorithms implemented in software. POOKA uses a commercially available reconfigurable computing board that plugs into standard Windows workstations.

Afreet exploits recent advances in computational machine learning theory, combining adaptive spatio-spectral image processing with a powerful support vector machine (SVM) supervised classifier to process imagery and image-like signals.

Zeus specializes in signal processing, using evolutionary computational techniques to build signal classification algorithms. Zeus is the newest member of the ISIS suite of toolmakers.