Complex Wavelet Structural Similarity quality measures for compressively sensing SAR images

Russel Stuart Daries, Amit Kumar Mishra

Research output: Chapter in Book/Report/Conference proceedingConference Proceeding (Non-Journal item)

Abstract

The field of Compressive Sampling (CS) has seen much development and growth in the past decade. It has successfully been applied in various fields related to radar, especially in Synthetic Aperture Radar (SAR) imaging. The aim of this paper is to demonstrate the frailties associated with the Normalized Root Mean Square Error (NRMSE) and Structural Similarity Index Measure (SSIM) [1] metrics in conveying the error present in the reconstructed SAR images. The Complex-Wavelet Structural Similarity Index (CW-SSIM) [2] is then proposed as an alternative metric to correctly quantify the quality of the recovered SAR images.

Original languageEnglish
Title of host publication2014 IEEE Radar Conference
Subtitle of host publicationFrom Sensing to Information, RadarCon 2014
PublisherIEEE Press
Pages892-895
Number of pages4
ISBN (Print)978-1-4799-2035-8
DOIs
Publication statusPublished - 19 May 2014
Externally publishedYes
Event2014 IEEE Radar Conference, RadarCon 2014 - Cincinnati, OH, United States of America
Duration: 19 May 201423 May 2014

Publication series

NameIEEE National Radar Conference - Proceedings
ISSN (Print)1097-5659

Conference

Conference2014 IEEE Radar Conference, RadarCon 2014
Country/TerritoryUnited States of America
CityCincinnati, OH
Period19 May 201423 May 2014

Keywords

  • Compressive Sensing
  • SAR imaging
  • structural similarity

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