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

Kuan Yu Huang, Pei Yin Chen, Ching Ching Huang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationProceedings - 2020 International Computer Symposium, ICS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages370-375
Number of pages6
ISBN (Electronic)9781728192550
DOIs
Publication statusPublished - 2020 Dec
Event2020 International Computer Symposium, ICS 2020 - Tainan, Taiwan
Duration: 2020 Dec 172020 Dec 19

Publication series

NameProceedings - 2020 International Computer Symposium, ICS 2020

Conference

Conference2020 International Computer Symposium, ICS 2020
CountryTaiwan
CityTainan
Period20-12-1720-12-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Computational Mathematics

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