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Many airborne imaging systems contain two or more sensors, but they typically only allow the operator to view the output of one sensor at a time. Often the sensors contain complimentary information which could be of benefit to the operator and hence there is a need for image fusion. Previous papers by these authors have described the techniques available for image alignment and image fusion. This paper discusses the implementation of a real-time image alignment and fusion system in a police helicopter. The need for image fusion and the requirements of fusion systems to pre-align images is reviewed. The techniques implemented for image alignment and fusion will then be discussed. The hardware installed in the helicopter and the system architecture will be described as well as the particular difficulties with installing a 'black box' image fusion system with existing sensors. The methods necessary for field of view matching and image alignment will be described. The paper will conclude with an illustration of the performance of the image fusion system as well as some feedback from the police operators who use the equipment.

The use of multiple, high sensitivity sensors can be usefully exploited within military airborne enhanced vision systems (EVS) to provide enhanced situational awareness. To realise such benefits, the imagery from the discrete sensors must be accurately combined and enhanced prior to image presentation to the aircrew. Furthermore, great care must be taken to not introduce artefacts or false information through the image processing routines. This paper outlines developments made to a specific system that uses three collocated low light level cameras. As well as seamlessly merging the individual images, sophisticated processing techniques are used to enhance image quality as well as to remove optical and sensor artefacts such as vignetting and CCD charge smear. The techniques have been designed and tested to be robust across a wide range of scenarios and lighting conditions, and the results presented here highlight the increased performance of the new algorithms over standard EVS image processing techniques.

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Hand-held thermal imaging systems are an important tool for fire and rescue services conducting search and rescue tasks. However, in order to achieve wide-spread deployment the cost of such systems must be minimised, and this generally leads to reduced image quality. Within this paper the use of advanced image processing functions to increase the imaging system performance is discussed. Of particular note is the use and benefits of noise reduction and contrast enhancement. Results from a developed camera system are presented, and the performance gains are illustrated and discussed.