A spatially adaptive hybrid total variation model for image restoration under Gaussian plus impulse noise

作者：

Highlights：

• We propose a spatially adaptive hybrid total variation model for restoring images corrupted by blur and mixed Gaussian-impulse noise.

• We give a detailed description of our model.

• We present an effective alternating minimization algorithm for solving proposed model.

• We give a detail description of implement of the proposed algorithm and compare it with several state-of-the-art methods.

摘要

•We propose a spatially adaptive hybrid total variation model for restoring images corrupted by blur and mixed Gaussian-impulse noise.•We give a detailed description of our model.•We present an effective alternating minimization algorithm for solving proposed model.•We give a detail description of implement of the proposed algorithm and compare it with several state-of-the-art methods.

论文关键词：Mixed Gaussian-impulse noise,Combined L1/L2 data fidelity term,Hybrid total variation,Total variation and high-order total variation,Spatially adaptive parameters

论文评审过程：Received 14 April 2021, Revised 13 August 2021, Accepted 6 December 2021, Available online 21 December 2021, Version of Record 21 December 2021.

论文官网地址：https://doi.org/10.1016/j.amc.2021.126862