PISTA: Parallel Iterative Soft Thresholding algorithm for sparse image recovery
Contributo in Atti di convegno
Data di Pubblicazione:
2013
Abstract:
We present PISTA, a GPU-accelerated Iterative Soft Thresholding (IST) algorithm for sparse image recovery in Compressive Sensing applications. As the time required to recover an image increases with the number of pixels, GPU-acceleration enables to recover even large images in reasonable time. With respect to equivalent methods, IST-like algorithms have lower computational complexity per-iteration and lower memory requirements, plus the operations are inherently suitable for parallelization. Our experiments show that our algorithm enables a significant reduction in the time required to recover an image even over a highly-optimized CPU-only reference. © 2013 IEEE.
Tipologia CRIS:
04.01 Contributo in Atti di convegno
Keywords:
parallel algorithms; compressed sensing; computational complexity; graphics processing units; iterative methods
Elenco autori:
Ravazzi, Chiara
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