Deconvolution is an important technique in image processing that may be used to recover images that have been subjected to a blurring process, usually caused by atmospheric effects or limitations of the image capturing equipment. Noise in the image data means that the problem is ill-posed, and thus mathematically complex statistical estimation techniques must be employed. This complexity, and the high throughput levels required for video data, renders a real-time software implementation unfeasible, however the parallelism of FPGA devices makes them an ideal medium. In this paper an FPGA implementation of an accelerated Richardson-Lucy deconvolution algorithm will be presented. The design uses multistage separable filters as a hardware efficient means of implementing the several large 2D convolutions that are required. The results show that real-time full scene deconvolution is viable with today's FPGA technology.

The aim of image fusion is to combine multiple images (from one or more sensors) into a single composite image that retains all useful data without introducing artefacts. Pattern-selective techniques attempt to identify and extract whole features in the source images to use in the composite. These techniques usually rely on multiresolution image representations such as Gaussian pyramids, which are localised in both the spatial and spatial-frequency domains, since they enable identification of features at many scales simultaneously. This paper presents an FPGA implementation of pyramidal decomposition and subsequent fusion of dual video streams. This is the first reported instance of a hardware implementation of pattern-selective pyramidal image fusion. Use of FPGA technology has enabled a design that can fuse dual video streams (greyscale VGA, 30fps) in real-time, and provides approximately 100 times speedup over a 2.8GHz Pentium-4

The EC funded COMBINE Project has the objective of dramatically improving software development productivity by providing a holistic approach to component-based development of enterprise systems. It has a single, cohesive UML based modelling environment for all development stages. Business modelling is key to user satisfaction, business flexibility and survival. Today, some IT services are so crucial to a business that, without them, things do not just happen less well, they do not happen at all, with disastrous consequences. Business models must do more than provide the starting point for system models-they must become an integral part of a system model, from which code is generated. "Traditional" business modelling is generally done using modelling concepts and tools that are not optimised to linking to a system model. The COMBINE Project has overcome this problem in two ways-identifying a coherent minimum set of modelling concepts and discovering a way of representing these in UML. This had to be done in a way that allowed models to be equally comprehensible to business experts and system modellers. The paper describes the COMBINE Team's approach to these problems, covering the structure of a business model, a minimum set of modelling concepts, use of UML "out of the box" and showing how a business model can be structured to provide the mapping between real world business concepts and software artifacts.