Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
The cell broadband engine: exploiting multiple levels of parallelism in a chip multiprocessor
International Journal of Parallel Programming
Wavelet based noise reduction by identification of correlations
DAGM'06 Proceedings of the 28th conference on Pattern Recognition
Image decomposition via the combination of sparse representations and a variational approach
IEEE Transactions on Image Processing
Image Denoising Via Sparse and Redundant Representations Over Learned Dictionaries
IEEE Transactions on Image Processing
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Patch-based approaches in imaging require heavy computations on many small sub-blocks of images but are easily parallelizable since usually different sub-blocks can be treated independently. In order to make these approaches useful in practical applications efficient algorithms and implementations are required. Newer architectures like the Cell Broadband Engine Architecture (CBEA) make it even possible to come close to real-time performance for moderate image sizes. In this article we present performance results for image denoising on the CBEA. The image denoising is done by finding sparse representations of signals from a given overcomplete dictionary and assuming that noise cannot be represented sparsely. We compare our results with a standard multicore implementation and show the gain of the CBEA.