Video quality prediction using a 3D dual-tree complex wavelet structural similarity index

Authors:
K. Yonis;R. M. Dansereau
Affiliations:
Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada;Department of Systems and Computer Engineering, Carleton University, Ottawa, Ontario, Canada
Venue:
ICISP'10 Proceedings of the 4th international conference on Image and signal processing
Year:
2010

Citing 3
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Abstract

In this paper, we test the performance of the complex wavelet structural similarity index (CW-SSIM) using the 2D dual-tree complex wavelet transform (DT-CWT). Also, we propose using a 3D DT-CWT with the CW-SSIM algorithm, to predict the quality of digital video signals. The 2D algorithm was tested against the LIVE image database and has shown higher correlation with the subjective results than peak signal-to-noise ratio (PSNR), structural similarity (SSIM), and the initial steerable pyramid implementation of CW-SSIM. The proposed 3D DT-CWT implementation of the CW-SSIM is tested against a set of subjectively scored video sequences from the video quality experts group's (VQEG) multimedia (MM) project and gave promising results. Both implementations were validated to be good quality assessment tools to be embedded with DT-CWT based image and video denoising algorithms as well as DT-CWT image and video coding algorithms.