Residual whiteness principle for automatic parameter selection in ℓ₂-ℓ₂ image super-resolution problems

2021/04/02 by Monica Pragliola, Pragliola, Monica, Luca Calatroni +5
Computer Science · Mathematics · #Advanced Image Processing Techniques #FOS: Mathematics #Image and Signal Denoising Methods #Numerical Analysis (math.NA) #Numerical methods in inverse problems

paper · pdf · doi:10.48550/arxiv.2104.01001

openalex publication_date 2021/04/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We propose an automatic parameter selection strategy for variational image super-resolution of blurred and down-sampled images corrupted by additive white Gaussian noise (AWGN) with unknown standard deviation. By exploiting particular properties of the operators describing the problem in the frequency domain, our strategy selects the optimal parameter as the one optimising a suitable residual whiteness measure. Numerical tests show the effectiveness of the proposed strategy for generalised ℓ₂-ℓ₂ Tikhonov problems.

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