Adaptive vector filtering with low computational complexity for image sensor applications

Chunmei Li, Kyu Young Kim, Young Jae Min, Chae Sung Kim, Soo Won Kim

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

Abstract

In this paper, a new adaptive vector filtering method with low computational complexity for image sensor applications is presented. The alternation between the ASDDF and the AVMF in the dependence on the order-statistics theory reduces the computational complexity. In addition, the proposed method provides excellent detection of noisy pixels and removes both chromatic and achromatic noisy pixels.

Original languageEnglish
Title of host publication2010 Symposium on Photonics and Optoelectronic, SOPO 2010 - Proceedings
DOIs
Publication statusPublished - 2010
EventInternational Symposium on Photonics and Optoelectronics, SOPO 2010 - Chengdu, China
Duration: 2010 Jun 192010 Jun 21

Publication series

Name2010 Symposium on Photonics and Optoelectronic, SOPO 2010 - Proceedings

Other

OtherInternational Symposium on Photonics and Optoelectronics, SOPO 2010
Country/TerritoryChina
CityChengdu
Period10/6/1910/6/21

Keywords

  • Adaptive vector filter
  • Image sensor
  • Impulse noise
  • Order-statistics theory

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Electronic, Optical and Magnetic Materials

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