Adaptive Lattice-Aware Image Demosaicking Using Global and Local Information

Ji Soo Kim, Keunsoo Ko, Chang Su Kim

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

Abstract

A novel approach for image demosaicking based on adaptive lattice-aware filter (ALF) and global refinement unit (GRU) is proposed in this work. We generate ALFs dynamically, which are adaptive to positions of pixels within color lattices in a color filter array, to obtain a locally demosaicked image. We then refine the locally demosaicked image using GRU to exploit global information, as well as local information. To extend the receptive fields efficiently, we adopt dilated convolutions in GRU. Experimental results demonstrate that the proposed algorithm provides the state-of-the-art performances in standard demosaicking datasets.

Original languageEnglish
Title of host publication2020 IEEE International Conference on Image Processing, ICIP 2020 - Proceedings
PublisherIEEE Computer Society
Pages483-487
Number of pages5
ISBN (Electronic)9781728163956
DOIs
Publication statusPublished - 2020 Oct
Event2020 IEEE International Conference on Image Processing, ICIP 2020 - Virtual, Abu Dhabi, United Arab Emirates
Duration: 2020 Sep 252020 Sep 28

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2020-October
ISSN (Print)1522-4880

Conference

Conference2020 IEEE International Conference on Image Processing, ICIP 2020
Country/TerritoryUnited Arab Emirates
CityVirtual, Abu Dhabi
Period20/9/2520/9/28

Keywords

  • Bayer pattern
  • Demosaicking
  • adaptive filters
  • convolutional neural networks

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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