Next Article in Journal
Piezoelectric Response of Multi-Walled Carbon Nanotubes
Previous Article in Journal
Intermetallic Growth and Interfacial Properties of the Grain Refiners in Al Alloys
Open AccessArticle

Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach

by Qing Li 1,* and Steven Y. Liang 1,2
1
College of Mechanical Engineering, Donghua University, Shanghai 201620, China
2
George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0405, USA
*
Author to whom correspondence should be addressed.
Materials 2018, 11(4), 637; https://doi.org/10.3390/ma11040637
Received: 27 March 2018 / Revised: 11 April 2018 / Accepted: 17 April 2018 / Published: 20 April 2018
Microstructure images of metallic materials play a significant role in industrial applications. To address image degradation problem of metallic materials, a novel image restoration technique based on K-means singular value decomposition (KSVD) and smoothing penalty sparse representation (SPSR) algorithm is proposed in this work, the microstructure images of aluminum alloy 7075 (AA7075) material are used as examples. To begin with, to reflect the detail structure characteristics of the damaged image, the KSVD dictionary is introduced to substitute the traditional sparse transform basis (TSTB) for sparse representation. Then, due to the image restoration, modeling belongs to a highly underdetermined equation, and traditional sparse reconstruction methods may cause instability and obvious artifacts in the reconstructed images, especially reconstructed image with many smooth regions and the noise level is strong, thus the SPSR (here, q = 0.5) algorithm is designed to reconstruct the damaged image. The results of simulation and two practical cases demonstrate that the proposed method has superior performance compared with some state-of-the-art methods in terms of restoration performance factors and visual quality. Meanwhile, the grain size parameters and grain boundaries of microstructure image are discussed before and after they are restored by proposed method. View Full-Text
Keywords: image restoration; KSVD dictionary; smoothing penalty sparse representation (SPSR); microstructure images; aluminum alloy 7075 (AA7075) material image restoration; KSVD dictionary; smoothing penalty sparse representation (SPSR); microstructure images; aluminum alloy 7075 (AA7075) material
Show Figures

Figure 1

MDPI and ACS Style

Li, Q.; Liang, S.Y. Microstructure Images Restoration of Metallic Materials Based upon KSVD and Smoothing Penalty Sparse Representation Approach. Materials 2018, 11, 637.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop