Image Denoising with Overlapping Group Sparsity and Second Order Total Variation Regularization

We propose an image denoising method by combining overlapping group sparsity and second-order total variation regularization. The method is named OGS-SOTV (image denoising method based on Overlapping Group Sparsity and Second-Order Total Variation regularization). The method utilizes performance of...

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Bibliographic Details
Published in2019 6th NAFOSTED Conference on Information and Computer Science (NICS) pp. 370 - 374
Main Authors Hue, Nguyen Minh, Thanh, Dang N. H., Thanh, Le Thi, Ngoc Hien, Nguyen, Surya Prasath, V. B.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2019
Subjects
Computer science
Gaussian noise
Image denoising
Image quality
Image restoration
Measurement
Noise reduction
overlapping group sparsity
Parameter estimation
regularization
total variation
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DOI10.1109/NICS48868.2019.9023801

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Summary:We propose an image denoising method by combining overlapping group sparsity and second-order total variation regularization. The method is named OGS-SOTV (image denoising method based on Overlapping Group Sparsity and Second-Order Total Variation regularization). The method utilizes performance of noise removal of overlapping group sparsity and performance of artifacts elimination of second-order total variation. A regularization parameter estimation is also proposed to implement the method automatically. In experiments, we compare denoising results of OGS-SOTV with ones of other similar methods. Results confirmed that OGS-SOTV works effectively and outperforms other similar denoising methods.
DOI:10.1109/NICS48868.2019.9023801