A Parallel Strategies for 2-D Lifting Wavelet Transform Using GPU

Lei Wang, Hongying Liu, Li Sun, Mei Zhou, Quanjie Zhuang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Lifting Wavelet Transform has a huge number of applications in image-processing techniques, it has been applied in field like image compression, fusion, de-noising, et al, but for large scale image, the algorithm is too slow to meet the real-time requirements. To solve this problem, this work proposed a parallel strategy based on GPU for 2-D lifting wavelet transform. Through the performance test and analysis, the proposed lifting scheme achieve considerable speedups compared with CPU version for the same image size.

Original languageEnglish
Title of host publicationProceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
EditorsQingli Li, Lipo Wang
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728148526
DOIs
StatePublished - Oct 2019
Event12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019 - Huaqiao, China
Duration: 19 Oct 201921 Oct 2019

Publication series

NameProceedings - 2019 12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019

Conference

Conference12th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2019
Country/TerritoryChina
CityHuaqiao
Period19/10/1921/10/19

Keywords

  • CUDA
  • GPU
  • image processing
  • lifting wavelet
  • parallel computation

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