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Journal of Vibration Testing and System Dynamics

C. Steve Suh (editor), Pawel Olejnik (editor),

Xianguo Tuo (editor)

Pawel Olejnik (editor)

Lodz University of Technology, Poland


C. Steve Suh (editor)

Texas A&M University, USA


Xiangguo Tuo (editor)

Sichuan University of Science and Engineering, China


Image Details Enhancement Method via Spectrum Total Variation

Journal of Vibration Testing and System Dynamics 5(2) (2021) 195--205 | DOI:10.5890/JVTSD.2021.06.007

Liu Chen$^{1,2}$, Zhi-Shuang Xue$^{1,2}$ , Ming-Ju Chen$^{1,2}$

$^{1}$ School of Automation and Information Engineering, Sichuan University of Science & Engineering, Zigong 643000, China

$^{2}$ Artificial Intelligence Key Laboratory of Sichuan Province, Sichuan University of Science and Engineering, Zigong 643000, China

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In order to enhance the texture details of images and preserve the complete structure of images, we propose a novel image detail enhancement method based on spectral total variation, which combines the total variation method and spectral analysis method. Firstly, the total variation flow, as a non-ideal high-pass filter, decomposes image and obtains the spectral characteristics of different time scales in the transform domain. The transform domain can be regarded as a frequency domain. Then, we construct a special filter in the transform domain, and the spectrum features are filtered and enhanced by the filter. Finally, according to the proposed reconstruction method, the filtering results in the transform domain are inversely converted to the spatial domain, that is, the final enhanced image is obtained. The experimental results show that the proposed spectral total variation method can effectively use the spectral information of the image to enhance the local details, so that the enhanced image can obtain more prominent texture information, while maintaining the integrity of the image structure.


This research was supported in part by the Project of Sichuan Department of Science and Technology under Grant 2017 GZ0303, in part by Special Fund for Training High Level Innovative Talents of Sichuan University of Science and Engineering under Grant B12402005, Grant 2018RCL21. and in part by the Opening Project of Key Laboratory of Higher Education of Sichuan Province for Enterprise Informationalization and Internet of Things under Grant 2019WZY04.


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