Flexible signal processing on programmable platforms are increasingly important for consumer electronic applications and others. scalable video algorithms (SVAs) using novel priority processing can guarantee real-time...
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Flexible signal processing on programmable platforms are increasingly important for consumer electronic applications and others. scalable video algorithms (SVAs) using novel priority processing can guarantee real-time performance on programmable platforms even with limited resources. Dynamic resource allocation is required to maximize the overall output quality of independent, competing priority processing algorithms that are executed on a shared platform. In this paper, we describe basic mechanisms for dynamic resource allocation and compare the performance of different implementations on a general purpose platform(1).
Consumer electronic products are increasingly becoming more open and flexible, which is achieved by replacing dedicate, single-function hardware components by software components running on programmable platforms. Sca...
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Consumer electronic products are increasingly becoming more open and flexible, which is achieved by replacing dedicate, single-function hardware components by software components running on programmable platforms. scalable video algorithms (SVAs) using the novel principle of priority processing can guarantee real-time performance on these platforms even with limited resources. In this paper we describe the mapping of a priority-processing application on an embedded consumer platform comprising a general purpose processor and multiple stream processing elements. An application comprises one or more independent, competing priority-processing algorithms. These SVAs have a single, dedicated streaming processor at their disposal. Dynamic resource allocation is required to maximize the overall output quality of SVAs that are executed on a shared platform. To enable real-time processing of individual SVAs, we compare the performance of different implementations for dynamic-resource-allocation mechanisms. Finally, we show that priority processing achieves real-time performance even under tight resource constraints(1).
Today's consumer electronic devices feature multiple applications which have to share scarcely available resources. We consider a priority-processing-based video application, which comprises multiple scalable vide...
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Today's consumer electronic devices feature multiple applications which have to share scarcely available resources. We consider a priority-processing-based video application, which comprises multiple scalable video algorithms (SVAs) that are executed on a shared, virtual platform. This application is given a guaranteed processor share by means of a constant-bandwidth server (CBS). A decision scheduler distributes the assigned processor share among the SVAs on a time-slot basis, with the aim to maximize their overall output quality. To correctly distribute this processor share based on fixed-sized time slots, we introduce the concept of a virtual timer. This timer only advances when its associated virtual platform is executing. Because priority processing can guarantee real-time performance even under fluctuating load, we apply a resource reclaiming mechanism to our CBS which makes it possible to efficiently exploit spare processor time(1).
Complexity scalablealgorithms are capable of trading resource usage for output quality in a near-optimal way. We present a complexity scalable motion estimation algorithm based on the 3-D recursive search block match...
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ISBN:
(纸本)0819444111
Complexity scalablealgorithms are capable of trading resource usage for output quality in a near-optimal way. We present a complexity scalable motion estimation algorithm based on the 3-D recursive search block matcher. We introduce data prioritizing as a new approach to scalability. With this approach, we achieve a near-constant complexity and a continuous quality-resource distribution. While maintaining acceptable quality, it is possible to vary the resource usage from below 1 match-error calculation per block on the average to more than 5 match-error calculations per block on the average.
A method for scalable motion compensated up-conversion of video sequences is proposed. By computing suitable objective quality estimates, (which show a high correlation with subjective quality scores), the method allo...
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ISBN:
(纸本)0819444111
A method for scalable motion compensated up-conversion of video sequences is proposed. By computing suitable objective quality estimates, (which show a high correlation with subjective quality scores), the method allows to predict the resources needed to up-convert a given input video sequence achieving a certain visual quality of the output video sequence. This method permits to dynamically change the resource utilisation in a way which is optimal for the system, e.g. for a programmable platform for media processing.
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