Journal of South China University of Technology (Natural Science Edition) ›› 2021, Vol. 49 ›› Issue (6): 109-121.doi: 10.12141/j.issn.1000-565X.200231

Special Issue: 2021年电子、通信与自动控制

• Electronics, Communication & Automation Technology • Previous Articles     Next Articles

Edge-Preserving Image Smoothing Algorithm Based on Reweighted l1 Norm

SONG Yu SUN Wenyun   

  1. College of Electronics and Information Engineering∥Shenzhen Key Laboratory of Media Security∥Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen 518060, Guangdong, China
  • Received:2020-05-13 Revised:2020-08-14 Online:2021-06-25 Published:2021-06-01
  • Contact: 宋昱(1988-),男,博士,主要从事图像处理、机器学习方面的研究。 E-mail:songy@szu.edu.cn
  • About author:宋昱(1988-),男,博士,主要从事图像处理、机器学习方面的研究。
  • Supported by:
    Supported by the China Postdoctoral Science Foundation(2019M663068)

Abstract: Edge-preserving image smoothing is a key preprocessing step of many computer vision and graphics algorithms. Edge-preserving image smoothing algorithm based on l1 norm outperforms many existing image smoothing algorithms. However, there are still many remaining textures in the smoothed results. In order to improve the smoothing effect of the algorithm, a new image smoothing algorithm based on reweighted l1 norm was proposed. The proposed algorithm combines the original l1 norm-based image smoothing algorithm and reweighed l1 norm minimization. The solution was made sparser through the reweighting method. The performance of the algorithm was evaluated through experiments. Experimental results show that, compared to the original l1 norm-based image smoothing algorithm and several other existing image smoothing algorithms, the proposed algorithm can smooth images very effectively and there is little texture remained in the smoothed results. Using reweighted l1 norm can improve the smoothing effect of the original l1 norm-based image smoothing algorithm.

Key words: edge-preserving image smoothing, l1 norm, reweighted l1 norm, image smoothing results

CLC Number: