A low-complexity learning-based algorithm for joint application of demosaicking and up-scaling

Kuan Yu Huang, Pei Yin Chen, Ching Ching Huang

研究成果: Conference contribution

1 引文 斯高帕斯(Scopus)

摘要

This paper proposes a low-complexity algorithm based on machine learning to deal with demosaicking and upscaling processes simultaneously. First, the color difference planes are calculated to extract the edge orientation and reconstruct the missing channel of G. Then the correlation of neighboring pixels is adopted to reconstruct the missing channels of RB and refine reconstructed the color planes. Finally, a novel machine learning structure is employ to up-scale image by optical interpolation kernels on the basis of designate feature descriptor. The refined operation and machine learning structure are two crucial contribution in this paper, which bring about decrease of the combination error and improvement of reconstructed quality. In experimental result, it is confirmed that the proposed method gets better reconstructed quality with lower cost of calculation than previous related methods.

原文English
主出版物標題Proceedings - 2020 International Computer Symposium, ICS 2020
發行者Institute of Electrical and Electronics Engineers Inc.
頁面370-375
頁數6
ISBN(電子)9781728192550
DOIs
出版狀態Published - 2020 12月
事件2020 International Computer Symposium, ICS 2020 - Tainan, Taiwan
持續時間: 2020 12月 172020 12月 19

出版系列

名字Proceedings - 2020 International Computer Symposium, ICS 2020

Conference

Conference2020 International Computer Symposium, ICS 2020
國家/地區Taiwan
城市Tainan
期間20-12-1720-12-19

All Science Journal Classification (ASJC) codes

  • 人工智慧
  • 電腦網路與通信
  • 電腦科學應用
  • 資訊系統
  • 資訊系統與管理
  • 計算數學

指紋

深入研究「A low-complexity learning-based algorithm for joint application of demosaicking and up-scaling」主題。共同形成了獨特的指紋。

引用此