Complex Wavelet Structural Similarity quality measures for compressively sensing SAR images

Author

Daries, Russel Stuart ; Mishra, Akhilesh Kumar

Author_Institution

Electr. Eng. Dept., Univ. of Cape Town, Cape Town, South Africa

fYear

2014

fDate

19-23 May 2014

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.

Keywords

compressed sensing; image reconstruction; mean square error methods; radar imaging; synthetic aperture radar; wavelet transforms; CW-SSIM; NRMSE; SAR imaging; SSIM metrics; complex-wavelet structural similarity index; compressive sampling; comrpessively sensing SAR images; normalized root mean square error; reconstructed SAR images; recovered SAR images; structural similarity index measure; synthetic aperture radar imaging; Compressed sensing; Distortion measurement; Equations; Image coding; Image reconstruction; Synthetic aperture radar; Compressive Sensing; SAR imaging; structural similarity;

fLanguage

English

Publisher

ieee

Conference_Titel

Radar Conference, 2014 IEEE

Conference_Location

Cincinnati, OH

Print_ISBN

978-1-4799-2034-1

Type

conf

DOI

10.1109/RADAR.2014.6875717

Filename

6875717