Reconfigurable computing for shape-adaptive video processing

Abstract

Various reconfigurable computing strategies are examined regarding their suitability for implementing shape-adaptive video processing algorithms of typical object-oriented multimedia applications. The utilisation of reconfigurability at different levels is investigated and the implications of designing reconfigurable shape-adaptive video processing circuits are addressed. Simple models for representing arbitrarily shaped objects and for mapping them into object-specific hardware designs are developed. Based on these models, several design and reconfiguration strategies, targeting an efficient mapping of shape-adaptive video processing tasks to a given reconfigurable computing architecture, are investigated. A number of real applications are analysed to study the trade-offs between these strategies. These include a shape-adaptive discrete cosine transform characterised by a limited number of different data-dependent computations and a shape-adaptive template matching method consisting of a virtually unlimited number of different computation possibilities. It is argued that shape-adaptive video processing algorithms with a relatively small number of different configuration contexts can often be more efficiently implemented as a static or multiconfiguration design, while a design employing dynamic or partial reconfiguration will be more suitable or even necessary if the number of different computation possibilities is relatively large.