Title :
A block-iterative surrogate constraint splitting method for quadratic signal recovery
Author :
Combettes, Patrick L.
Author_Institution :
Lab. Jacques-Louis Lions, Univ. Pierre et Marie Curie, Paris, France
fDate :
7/1/2003 12:00:00 AM
Abstract :
A block-iterative parallel decomposition method is proposed to solve general quadratic signal recovery problems under convex constraints. The proposed method proceeds by local linearizations of blocks of constraints, and it is therefore not sensitive to their analytical complexity. In addition, it naturally lends itself to implementation on parallel computing architectures due to its flexible block-iterative structure. Comparisons with existing methods are carried out, and the case of inconsistent constraints is also discussed. Numerical results are presented.
Keywords :
deconvolution; image restoration; iterative methods; parallel architectures; quadratic programming; reviews; signal reconstruction; signal restoration; analytical complexity; block-iterative optimization; block-iterative parallel decomposition method; block-iterative structure; block-iterative surrogate constraint splitting; convex constraints; digital image restoration; inconsistent constraints; local linearizations; parallel computing architectures; quadratic programming; quadratic signal recovery; signal deconvolution; signal reconstruction; signal restoration; Computer architecture; Deconvolution; Equations; Filtering; Hilbert space; Noise measurement; Parallel processing; Quadratic programming; Signal analysis; Signal restoration;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2003.812846
