Image registration and fusion system based on GPU

Seung Hun Yoo, Chang Sung Jeong

Research output: Contribution to journalArticlepeer-review


Graphics processing unit (GPU) has surfaced as a high-quality platform for computer vision-related systems. In this paper, we propose a straightforward system consisting of a registration and a fusion method over GPU, which generates good results at high speed, compared to non-GPU-based systems. Our GPU-accelerated system utilizes existing methods through converting the methods into the GPU-based platform. The registration method uses point correspondences to find a registering transformation estimated with the incremental parameters in a coarse-to-fine way, while the fusion algorithm uses multi-scale methods to fuse the results from the registration stage. We evaluate performance with the same methods that are executed over both CPU-only and GPU-mounted environment. The experiment results present convincing evidences of the efficiency of our system, which is tested on a few pairs of aerial images taken by electro-optical and infrared sensors to provide visual information of a scene for environmental observatories.

Original languageEnglish
Pages (from-to)173-189
Number of pages17
JournalJournal of Circuits, Systems and Computers
Issue number1
Publication statusPublished - 2010 Feb


  • GPU-based system
  • Graphics hardware
  • Image registration
  • Multi-scale image fusion

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering


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