Edge detection for millimeter-wave images based on curvelet transform

Hui Qian Du*, Fei Gu, Wen Bo Mei

*Corresponding author for this work

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

Abstract

The millimeter-wave images have low resolution and heavy noise. Hence it is hard to detect the edges in such images. A detection scheme based on curvelet transform is proposed. The idea is to suppress noise through Wrapping algorithm of curvelet transform at first, then determine gradient amplitude of pixels. At last the non-maximum and double threshold method are used to obtain the edges. The experiments show that clear edges of human and object images in millimeter-wave images can be detected efficiently, and the scheme implements fast.

Original languageEnglish
Title of host publicationInternational Symposium on Photoelectronic Detection and Imaging 2007
Subtitle of host publicationRelated Technologies and Applications
DOIs
Publication statusPublished - 2008
EventInternational Symposium on Photoelectronic Detection and Imaging, ISPDI 2007: Related Technologies and Applications - Beijing, China
Duration: 9 Sept 200712 Sept 2007

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6625
ISSN (Print)0277-786X

Conference

ConferenceInternational Symposium on Photoelectronic Detection and Imaging, ISPDI 2007: Related Technologies and Applications
Country/TerritoryChina
CityBeijing
Period9/09/0712/09/07

Keywords

  • Curvelet transform
  • Edge detection
  • Millimeter-wave image
  • The warping algorithm

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