Neural network deinterlacing using multiple fields

Hyunsoo Choi, Eunjae Lee, Chulhee Lee

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

6 Citations (Scopus)


In this paper, we proposed a deinterlacing algorithm using neural networks for conversion of interlaced videos to progressive videos. The proposed method uses multiple fields: a previous field, a current field, and a next field. Since the proposed algorithm uses multiple fields, the neural network is able to take into account the motion pattern which might exists in adjacent fields. Experimental results demonstrate that the proposed algorithm provides better performances than existing neural network deinterlacing algorithms that uses a single field.

Original languageEnglish
Title of host publicationIntelligent Computing in Signal Processing and Pattern Recognition
Subtitle of host publicationInternational Conference on Intelligent Computing, ICIC 2006
EditorsDe-Shaung Huang, Kang Li, George William Irwin
Number of pages6
Publication statusPublished - 2006

Publication series

NameLecture Notes in Control and Information Sciences
ISSN (Print)0170-8643

All Science Journal Classification (ASJC) codes

  • Library and Information Sciences


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