ENVI-Based Patent Opens the Door to Near Real-Time Image Processing on Remote Platforms

Customer Challenge

Members of the Johns Hopkins University Applied Physics Laboratory needed to find alternative uses for common gridded weather data to advance civilian and military operations, such as search and rescue missions.

Solution Achieved

Weather data collected from various sources, such as balloons and satellites, have been used for many decades, and has recognized immeasurable success in advancing weather forecasting and climate modeling. Now, the US military is interested in finding ways to repurpose that data for less traditional, more advanced applications.

When Marc Kolodner joined the Johns Hopkins University Applied Physics Laboratory (JHU/APL), he was tasked with finding alternative uses for common gridded weather data, and proving how the data, in conjunction with specialized software, could become a valuable asset in unconventional scenarios outside of forecasting and prediction. After performing extensive weather-related research and developing several advanced applications using IDL^® and ENVI^®, he ultimately patented a novel approach to hyperspectral image exploitation that will have an enormous positive impact on both military and civilian operations, including search and rescue and first response to disaster situations.

Patenting the new spectral analysis process began when Kolodner and others at JHU/APL developed and perfected an IDL-based software solution that allows any user to easily read, extract, and interact with weather data acquired from the Air Force Weather Agency (AFWA) directly from their computer screen. The user-friendly software application, called the Atmospheric Profile Generator, consists of “modules” that perform various weather-related functions that are used for non-traditional forecasting activities. Some military-focused uses include a module that allows the user to compute the line-of-sight loss of transmission over various wavelengths due to atmospheric absorption, a process called a transmittance calculation. Another module, created in partnership with University of Alaska, allows the user to predict when, and under which weather conditions, a contrail from an aircraft might form.

In search of even more constructive uses for the AFWA data, and after many other successful development initiatives, Kolodner recognized that hosts of other critical scenarios require processing and analyzing spectral images more quickly and efficiently. He ultimately patented the ENVI-based method, which incorporates his original IDL-based Atmospheric Profile Generator application and a well-known radiative transfer code MODTRAN, and ultimately created a unique way to predict spectral signatures for detection in advance of an operation – such as search and rescue – taking place.

The patented process, called the Spectral Radiance Generator, was developed under the assumption that if aircraft or satellite hyperspectral sensors are essentially “fed” spectral signature information in advance of collecting data, then on-board processors would be able to find items with that signature in near real time. The ENVI software combines the Collection, Sensor, Signature, and Environmental specifications to model what the sensor would measure if the items to be detected were present in the scene. Specific spectra are provided for items that are fully illuminated by the sun and even items that are shadowed by natural or man-made obstacles.

Kolodner’s method allows remote sensors to recognize unique signatures in an image scene, saving time and resources over the accepted current practice, which requires that data be collected and taken back to a ground control station for spectral signature analysis. Only once the analysis is complete can an image analyst determine if any items matching particular spectral signatures appear in an imaged scene.

Kolodner gives a concrete example of a search and rescue operation in which the process would save valuable time and resources compared with the standard practice. In the example, a team needs to find a missing person known to be driving a certain type of vehicle. On the ground, ENVI users generate the at-sensor spectral signature of the paint on the vehicle using the Spectral Radiance Generator. That team transmits the spectral information to a team onboard a remote aircraft platform which flies over a candidate scene and collects the hyperspectral imagery. The data is processed immediately with the uploaded spectra, allowing them to detect the vehicle paint if present.

“The ENVI software runs processes quickly on the ground, so, you don’t have to take hours to optimize and run an application,” Kolodner says. “Within minutes you can generate the spectral information in advance of an operation.”

In the future, Kolodner and the rest of the JHU/APL team will continue to find new ways to repurpose and maximize weather data, both for civilian and military operations. To learn more, visit their website at http://sd-www.jhuapl.edu/UPOS/SRG.

Benefits

• Both civilian and military operations now have a quicker, more efficient way to identify objects from remote sensors
• Kolodner's method saves time and resources compared with traditional methods
• ENVI's quick processing capabilities and superior spectral processing routines allowed the team to create a unique solution