Abstract | ||
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The ease of image storage and transmission in modern applications would be unfeasible without compression, which converts high-resolution images into a relatively small set of significant transform coefficients. Due to the specific content of many real-world images they are highly sparse in an appropriate orthonormal basis. The inherent property of compressed sensing (CS) the- ory working simultaneously as a sensing and compression protocol, using a small subset of random incoherent projection coefficients, enables a poten- tially significant reduction in the sampling and computation costs of images favoring its use in real-time applications which do not require an excellent reconstruction performance. In this paper, we develop a Bayesian CS (BCS) approach for obtaining highly sparse representations of images based on a set of noisy CS measurements, where the prior belief that the vector of pro- jection coefficients should be sparse is enforced by fitting directly its prior probability distribution by means of a Gaussian Scale Mixture (GSM). The experimental results show that our proposed method, when compared with norm-based constrained optimization algorithms, maintains the reconstruc- tion performance, in terms of the reconstruction error and the PSNR, while achieving an increased sparsity using much less basis functions. |
Year | DOI | Venue |
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2010 | 10.1109/ICASSP.2010.5495397 | Acoustics Speech and Signal Processing |
Keywords | Field | DocType |
data compression,image coding,Bayesian compressed sensing imaging,Gaussian scale mixture,image storage,image transmission,probability distribution,random incoherent projection coefficients,sparse representations | Iterative reconstruction,Pattern recognition,Computer science,Probability distribution,Orthonormal basis,Basis function,Artificial intelligence,Data compression,Prior probability,Compressed sensing,Constrained optimization | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4244-4296-6 | 978-1-4244-4296-6 | 3 |
PageRank | References | Authors |
0.43 | 9 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
George Tzagkarakis | 1 | 139 | 17.94 |
P. Tsakalides | 2 | 954 | 120.69 |