Q+A CENTER

The integration of multi-modality, multi-format image data is a key interest in imaging development and has for years been a central theme in efforts to increase military and security usage of image data. That does not mean that the impact is limited to the battlefield. Image fusion development may lead to increased capability in medical and scientific work as well as in industrial imaging.

New image-fusion techniques are on the horizon for many applications, according to Jonathan Schuler, Ph.D., of Logos Technologies (Arlington, VA). Schuler has more than 10 years experience in image processing of airborne and ground-based tactical imaging sensors -- particularly with multi-spectral infrared, low-light visible and ionizing radiation sensors. His own specialization includes high accuracy image registration and geo-location, statistical image restoration, image resolution enhancement, spatio-temporal video processing, radiometric calibration, multi-spectral image fusion, adaptive non-uniformity correction and sensor modeling and simulation.

Advanced Imaging: Please describe the types of image-fusion technology development and delivery in which Logos Technologies has been involved, and why?

Jonathon Schuler: Our work in image fusion centers on effective image-rendering techniques for human interpretation of multi-modality sensors, including infrared, low light, hyperspectral, SAR, PMMW and ionizing X-ray/gamma-ray imaging devices. Our motivation is analogous to the reasons why black-and-white RS-170 video continues to be an output format found on many contemporary sensors: certain "human in the loop" operations, such as sensor pointing and scene monitoring, require a convenient and readily interpretable graphical display. Color fusion of multiple, simultaneous imaging modes rendered on a digital display promises substantially improved cognition and situational awareness over, say, monochrome video viewed over a standard definition CRT monitor.

Advanced Imaging: Broadly speaking, where has the key progress been made, up to now, in integrating image data and making it useful, and what remain the biggest challenges?