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Video Quality Prediction Using a 3D Dual-Tree Complex Wavelet Structural Similarity Index

机译:使用3D双树复小波结构相似性指数的视频质量预测

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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.
机译:在本文中,我们使用2D双树复数小波变换(DT-CWT)测试复数小波结构相似性指标(CW-SSIM)的性能。另外,我们建议使用带有CW-SSIM算法的3D DT-CWT来预测数字视频信号的质量。该2D算法针对LIVE图像数据库进行了测试,与主观结果相比,与峰值信噪比(PSNR),结构相似性(SSIM)和CW-SSIM的初始可控金字塔实现相比,具有更高的相关性。针对视频质量专家组(VQEG)多媒体(MM)项目中的一组主观评分视频序列对CW-SSIM的拟议3D DT-CWT实现进行了测试,并给出了可喜的结果。两种实现方式均被验证为可嵌入基于DT-CWT的图像和视频降噪算法以及DT-CWT图像和视频编码算法的高质量评估工具。

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