Visual depth guided image rain streaks removal via sparse coding

Duan Yu Chen*, Chien Cheng Chen, Li Wei Kang

*此作品的通信作者

研究成果: 書貢獻/報告類型會議論文篇章

9 引文 斯高帕斯(Scopus)

摘要

Rain removal from an image is a challenging problem since no motion information can be obtained from successive images. In this work, an input image is first decomposed into low-frequency part and high-frequency part by using guided image filter. So that the rain streaks would be in the high-frequency part with non-rain textures, and then the high-frequency part is decomposed into a 'rain component' and a 'non-rain component' by performing dictionary learning and sparse coding. To separate rain streaks from high-frequency part, a hybrid feature set is exploited which includes histogram of gradient (HoG) and difference of depth (DoD). With the hybrid feature set applied, most rain streaks can be removed; meanwhile, non-rain components can be enhanced. Compared with the state-of-the-art method [12], our proposed approach shows that not only the rain components can be removed more effectively, but also the visual quality of restored images can be improved.

原文英語
主出版物標題ISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems
頁面151-156
頁數6
DOIs
出版狀態已發佈 - 2012
對外發佈
事件20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012 - Tamsui, New Taipei City, 臺灣
持續時間: 2012 十一月 42012 十一月 7

出版系列

名字ISPACS 2012 - IEEE International Symposium on Intelligent Signal Processing and Communications Systems

其他

其他20th IEEE International Symposium on Intelligent Signal Processing and Communications Systems, ISPACS 2012
國家/地區臺灣
城市Tamsui, New Taipei City
期間2012/11/042012/11/07

ASJC Scopus subject areas

  • 人工智慧
  • 電腦網路與通信
  • 訊號處理

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