@inproceedings{e9066f48029240dca05ce6e62cfa1f74,
title = "Complex Wavelet Structural Similarity quality measures for compressively sensing SAR images",
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 = "Compressive Sensing, SAR imaging, structural similarity",
author = "Daries, {Russel Stuart} and Mishra, {Amit Kumar}",
year = "2014",
month = may,
day = "19",
doi = "10.1109/RADAR.2014.6875717",
language = "English",
isbn = "978-1-4799-2035-8",
series = "IEEE National Radar Conference - Proceedings",
publisher = "IEEE Press",
pages = "892--895",
booktitle = "2014 IEEE Radar Conference",
address = "United States of America",
note = "2014 IEEE Radar Conference, RadarCon 2014 ; Conference date: 19-05-2014 Through 23-05-2014",
}