Image De-noising on Strip Steel Surface Defect Using Improved Compressive Sensing Algorithm

Dongyan Cui, Kewen Xia, Jingzhong Hou, Ahmad Ali

Abstract


De-noising for the strip steel surface defect image is conductive to the accurate detection of the strip steel surface defects. In order to filter the Gaussian noise and salt and pepper noise of strip steel surface defect images, an improved compressive sensing algorithm was applied to defect image de-noising in this paper. First, the improved Regularized Orthogonal Matching Pursuit algorithm was described. Then, three typical surface defects (scratch, scar, surface upwarping) images were selected as the experimental samples. Last, detailed experimental tests were carried out to the strip steel surface defect image de-noising. Through comparison and analysis of the test results, the Peak Signal to Noise Ratio value of the proposed algorithm is higher compared with other traditional de-noising algorithm, and the running time of the proposed algorithm is only26.6\% of that of traditional Orthogonal Matching Pursuit algorithms. Therefore, it has better de-noising effect and can meet the requirements of real-time image processing.

Keywords


compressive sensing; surface defects; image de-noising;

Full Text:

PDF


DOI: http://dx.doi.org/10.12928/telkomnika.v15i1.3164

Article Metrics

Abstract view : 217 times
PDF - 336 times

Refbacks

  • There are currently no refbacks.


Copyright (c) 2019 Universitas Ahmad Dahlan

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

TELKOMNIKA Telecommunication, Computing, Electronics and Control
ISSN: 1693-6930, e-ISSN: 2302-9293
Universitas Ahmad Dahlan, 4th Campus, 9th Floor, LPPI Room
Jl. Ringroad Selatan, Kragilan, Tamanan, Banguntapan, Bantul, Yogyakarta, Indonesia 55191
Phone: +62 (274) 563515, 511830, 379418, 371120 ext. 4902, Fax: +62 274 564604

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

View TELKOMNIKA Stats