全变差去噪
降噪
正规化(语言学)
图像去噪
模式识别(心理学)
计算机科学
非本地手段
变化(天文学)
算法
数学
图像(数学)
人工智能
物理
天体物理学
作者
Nguyen Minh Hue,Dang N. H. Thanh,Le Thi Thanh,Nguyễn Ngọc Hiền,V. B. Surya Prasath
标识
DOI:10.1109/nics48868.2019.9023801
摘要
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.
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