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Energy-Efficient and Portable Least Squares Prediction for Image Coding on a Mobile GPU
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Advisor(s)
Abstract(s)
Least squares prediction is a technique used to foresee pixel values during image coding by finding the minimum square error of neighbouring pixels. It has shown considerable quality gains especially for complex images with high variations
in pixel intensities. The drawback of this technique consists of high computational complexity, consuming the most significant part of processing time and resources available, which makes it difficult to implement in fast, lossy image coders. One challenge is therefore to reduce the computational time of this predictor, namely through the use of new parallel programming techniques, making it more attractive for state-of-the-art coder-decoders. Also, new algorithmic propositions are made, trying to reduce the time spent in exchange for rate-distortion performance. These
propositions are senseful since this predictor is used not only in lossless image coding, but also in lossy as well. Another aim of this article is to analyze energy efficiency among different types of platforms for this signal processing algorithm. Comparisons are provided on parallel computing processors ranging from very
powerful Graphics Computing Units (GPUs) to mobile General-Purpose GPUs.
Description
Keywords
Parallel processing Mobile GPU Energyefficiency Image Coding Least Squares Prediction
Pedagogical Context
Citation
P. Cordeiro, G. Falcao, P. Domingues, N. Rodrigues and S. Faria, "Energy-Efficient and Portable Least Squares Prediction for Image Coding on a Mobile GPU," 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP), St. Petersburg, Russia, 2017, pp. 237-240, doi: 10.1109/PDP.2017.97
Publisher
IEEE
CC License
Without CC licence