LSR based astronomical image denoising via adaptive dictionary learning

Motivated by local coordinate coding (LeC) theory in nonlinear manifold learning, we proposed a new image representation model called local sparse representation (LSR) for astronomical image denoising. Meanwhile, a fast approximated LSR method by first performing a K-nearest-neighbor search and then...

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Hauptverfasser: Yang, Afeng, Lu, Min, Teng, Shuhua, Sun, Jixiang
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Motivated by local coordinate coding (LeC) theory in nonlinear manifold learning, we proposed a new image representation model called local sparse representation (LSR) for astronomical image denoising. Meanwhile, a fast approximated LSR method by first performing a K-nearest-neighbor search and then solving a ℓ 1 optimization problem is presented under the guarantee of denoising performance. In addition, we incorporate the LSR model and adaptive dictionary learning into a unified optimization framework, explicitly establish the inner connection of them. Such processing allows us to simultaneously update sparse coding vectors and the dictionary by alternating-optimization method. Our experimental results have shown convincing improvements on astronomical image denoising.
DOI:10.1109/CVRS.2012.6421263