A software application, SIST, has been developed for the simulation of the video at the output of a thermal imager. The approach offers a more suitable representation than current identification (ID) range predictors do: the end user can
evaluate the adequacy of a virtual camera as if he was using it in real operating conditions. In particular, the ambiguity in the interpretation of ID range is cancelled. The application also allows for a cost-efficient determination of the optimal design of an imager and of its subsystems without over- or under-specification: the performances are known early in the development cycle, for targets, scene and environmental conditions of interest. The simulated image is also a powerful method for testing processing algorithms. Finally, the display, which can be a severe system limitation, is also fully
considered in the system by the use of real hardware components. The application consists in Matlab<sup>tm</sup> routines that
simulate the effect of the subsystems atmosphere, optical lens, detector, and image processing algorithms. Calls to
MODTRAN® for the atmosphere modeling and to Zemax for the optical modeling have been implemented. The realism of the simulation depends on the adequacy of the input scene for the application and on the accuracy of the subsystem
parameters. For high accuracy results, measured imager characteristics such as noise can be used with SIST instead of
less accurate models. The ID ranges of potential imagers were assessed for various targets, backgrounds and atmospheric conditions. The optimal specifications for an optical design were determined by varying the Seidel aberration coefficients to find the worst MTF that still respects the desired ID range.
Automated video monitoring of mobile objects is a growing trend in many sectors, especially in surveillance applications. Many research groups are addressing substantial efforts to develop autonomous applications able to recognize specified events. Reliability of such a system is mainly defined by its ability to extract and to track features of interest in image sequences. Since the capacity to perform this basic task is strongly related to changes in image
contrast, video monitoring units made up mono-spectral sensors offer limited performances in many situations. The best example of such a limitation is the uselessness of a visible CCD camera in low brightness scene. To overcome these shortcomings, we developed an acquisition unit including an uncooled VOx thermal camera (8-12 mm)and a High-Dynamic-Range-CMOS(R) color camera more suitable for outdoor applications. Unlike similar systems, we perform image registration at hardware level rather than at software level. Advantageous characteristics of such a design are presented in this paper. A simple framework is also proposed in order to achieve context-independent event extraction from color and thermal information.