Parallel transformation of K-SVD solar image denoising algorithm

Liang, Youwen; Tian, Yu; Li, Mei

doi:10.1117/12.2256495

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2019

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“…Applications of the K-SVD algorithm are discussed in a large number of papers in image denoising, image classification, audio processing, etc. [6,7,8,9].…”

Section: Introductionmentioning

confidence: 99%

Generalization of the K-SVD algorithm for minimization of β-divergence

Garcia-Mollá

Juan

Virtanen

et al. 2019

Digital Signal Processing

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In this paper, we propose, describe, and test a modification of the K-SVD algorithm. Given a set of training data, the proposed algorithm computes an overcomplete dictionary by minimizing the β-divergence (β >= 1) between the data and its representation as linear combinations of atoms of the dictionary, under strict sparsity restrictions. For the special case β = 2, the proposed algorithm minimizes the Frobenius norm and, therefore, for β = 2 the proposed algorithm is equivalent to the original K-SVD algorithm. We describe the modifications needed and discuss the possible shortcomings of the new algorithm.The algorithm is tested with random matrices and with an example based on speech separation.

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“…Applications of the K-SVD algorithm are discussed in a large number of papers in image denoising, image classification, audio processing, etc. [6,7,8,9].…”

Section: Introductionmentioning

confidence: 99%