Title :
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
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;
Conference_Titel :
Radar Conference, 2014 IEEE
Conference_Location :
Cincinnati, OH
Print_ISBN :
978-1-4799-2034-1
DOI :
10.1109/RADAR.2014.6875717
