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This paper addresses practical considerations for the implementation of algorithms developed to increase the image resolution from a video sequence by using techniques known in the specialized literature as super-resolution (SR). In order to achieve a low-cost implementation, the algorithms have been mapped onto a previously developed video encoder architecture. By re-using such architecture and performing only slight modifications on it, the need for specific, and usually high-cost, SR hardware is avoided. This modified encoder can be used either in native compression mode or in SR mode, where SR can be used to increase the image resolution over the sensor limits or as a smart way to perform electronic zoom, avoiding the use of high-power demanding mechanical parts. Two SR algorithms are presented and compared in terms of execution time, memory usage and quality. These algorithms features are analyzed from a real-time implementation perspective. The first algorithm follows an iterative scheme while the second one is a modified version where the iterative behavioural has been broken. The video encoder together with the new SR features constitutes an IP block inside Philips Research, upon which several System on Chip (SoC) platforms are being developed.

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Today, mechanical tracking systems have been downsized to allow them to be used in the field of airborne laser communications and in the military domain. Risley systems are used for this purpose, which work by directing a beam of light to a given target point, this procedure is commonly known as the inverse problem. In this paper, an analytical method, the geometric method, has been designed and developed to determine the beam steering in a Risley system and solve the inverse problem. The method focuses on different geometric shapes, like circumference or ellipse, that are described when the beam passes through the second prism. The accuracy and efficiency of the geometric method has been analysed and found to be faster than the two-step method. Furthermore, the geometric method has been implemented in an iterative process and an accuracy of up to 1 pm has been achieved. This high accuracy would allow the geometric method to be applied in fields such as lithography, stereolithography or 3D printers.

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