Performance Evaluation of Cross Correlation Functions Based on Correlation Filters

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

Abstract

This paper proposes performance evaluation of cross correlation (CC) functions using signal-to-noise ratio (SNR) and peak-to-correlation energy (PCE) from the viewpoint of correlation filters. Correlation functions can be thought as the output from the correlation filters. Maximizing SNR leads to matched filters, whereas maximizing PCE results in the inverse filters. We derive SNR and PCE of the classical CC functions in order to evaluate their performance as correlation functions.

Original languageEnglish
Title of host publicationProceedings of ISCIT 2021
Subtitle of host publication2021 20th International Symposium on Communications and Information Technologies: Quest for Quality of Life and Smart City
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages145-149
Number of pages5
ISBN (Electronic)9781665449588
DOIs
Publication statusPublished - 2021 Oct 19
Event20th International Symposium on Communications and Information Technologies, ISCIT 2021 - Virtual, Online, Japan
Duration: 2021 Oct 192021 Oct 22

Publication series

NameProceedings of ISCIT 2021: 2021 20th International Symposium on Communications and Information Technologies: Quest for Quality of Life and Smart City

Conference

Conference20th International Symposium on Communications and Information Technologies, ISCIT 2021
Country/TerritoryJapan
CityVirtual, Online
Period21/10/1921/10/22

Keywords

  • correlation filters
  • cross correlation functions
  • peak-to-correlation energy
  • signal-to-noise ratio

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Information Systems and Management

Fingerprint

Dive into the research topics of 'Performance Evaluation of Cross Correlation Functions Based on Correlation Filters'. Together they form a unique fingerprint.

Cite this