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Open AccessArticle

A Novel Image-Restoration Method Based on High-Order Total Variation Regularization Term

College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China
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Electronics 2019, 8(8), 867; https://doi.org/10.3390/electronics8080867
Received: 25 June 2019 / Revised: 30 July 2019 / Accepted: 1 August 2019 / Published: 5 August 2019
(This article belongs to the Special Issue Signal Processing and Analysis of Electrical Circuit)
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Abstract

This paper presents two new models for solving image the deblurring problem in the presence of impulse noise. One involves a high-order total variation (TV) regularizer term in the corrected total variation L1 (CTVL1) model and is named high-order corrected TVL1 (HOCTVL1). This new model can not only suppress the defects of the staircase effect, but also improve the quality of image restoration. In most cases, the regularization parameter in the model is a fixed value, which may influence processing results. Aiming at this problem, the spatially adapted regularization parameter selection scheme is involved in HOCTVL1 model, and spatially adapted HOCTVL1 (SAHOCTVL1) model is proposed. When dealing with corrupted images, the regularization parameter in SAHOCTVL1 model can be updated automatically. Many numerical experiments are conducted in this paper and the results show that the two models can significantly improve the effects both in visual quality and signal-to-noise ratio (SNR) at the expense of a small increase in computational time. Compared to HOCTVL1 model, SAHOCTVL1 model can restore more texture details, though it may take more time. View Full-Text
Keywords: image restoration; impulse noise; ADMM; HOCTVL1; spatially adapted regularization parameter image restoration; impulse noise; ADMM; HOCTVL1; spatially adapted regularization parameter
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Xiang, J.; Ye, P.; Wang, L.; He, M. A Novel Image-Restoration Method Based on High-Order Total Variation Regularization Term. Electronics 2019, 8, 867.

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