We present an algorithm for subpixel material identification that is invariant to the illumination and atmospheric conditions. The target material spectral reflectance is the only prior information required by the algorithm. A target material subspace model is constructed from the reflectance using a physical model and a background subspace model is estimated directly from the image. These two subspace models are used to compute maximum likelihood estimates for the target material component and the background component at each image pixel. These estimates form the basis of a generalized likelihood ratio test for subpixel material identification. We present experimental results using HYDICE imagery that demonstrate the utility of the algorithm for subpixel material identification under varying illumination and atmospheric conditions.
The Irma synthetic signature prediction code is being developed to facilitate the research and development of multisensor systems. Irma was one of the first high resolution Infrared (IR) target and background signature models to be developed for tactical weapon application. Originally developed in 1980 by the Munitions Directorate of the Air Force Research Laboratory (AFRL/MN), the Irma model was used exclusively to generate IR scenes. In 1988, a number of significant upgrades to Irma were initiated including the addition of a laser (or active) channel. This twochannel version was released to the user community in 1990. In 1992, an improved scene generator was incorporated into the Irma model, which supported correlated frame-to-frame imagery. A passive IR/millimeter wave (MMW) code was completed in 1994. This served as the cornerstone for the development of the co-registered active/passive IR/MMW model, Irma 4.0. In 2000, Irma version 5.0 was released which encompassed several upgrades to both the physical models and software. Circular polarization was added to the passive channel and the doppler capability was added to the active MMW channel. In 2002, the multibounce technique was added to the Irma passive channel. In the ladar channel, a user-friendly Ladar Sensor Assistant (LSA) was incorporated which provides capability and flexibility for sensor modeling. Irma 5.0 runs on several platforms including Windows, Linux, Solaris, and SGI Irix. Since 2000, additional capabilities and enhancements have been added to the ladar channel including polarization and speckle effect. Work is still ongoing to add time-jittering model to the ladar channel. A new user interface has been introduced to aid users in the mechanism of scene generation and running the Irma code. The user interface provides a canvas where a user can add and remove objects using mouse clicks to construct a scene. The scene can then be visualized to find the desired sensor position. The synthetic ladar signatures have been validated twice and underwent a third validation test near the end of 04. These capabilities will be integrated into the next release, Irma 5.1, scheduled for completion in the summer of FY05. Irma is currently being used to support a number of civilian and military applications. The Irma user base includes over 130 agencies within the Air Force, Army, Navy, DARPA, NASA, Department of Transportation, academia, and industry. The purpose of this paper is to report the progress of the Irma 5.1 development effort.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.