日本語フィールド
著者：HAJIME OMURA, TERUYA MINAMOTO題名：IMAGE QUALITY DEGRADATION ASSESSMENT BASED ON THE DUAL-TREE COMPLEX DISCRETE WAVELET TRANSFORM FOR EVALUATING DIGITAL IMAGEWATERMARKING発表情報：Proceedings of the 2016 International Conference on Wavelet Analysis and Pattern Recognition ページ: pp.270-275キーワード：概要：抄録：We propose a new image quality degradation assessment method for evaluating the quality of watermarked images based on the dual-tree complex discrete wavelet transform (DT-CDWT). The peak signal to noise ratio (PSNR) and structural similarity (SSIM) are widely used to evaluate image quality degradation resulting from embedding a digital watermark. However, they do not always correctly evaluate the image quality degradation in such cases since they use only the spatial domain. In contrast, our method, based on the dual-tree complex discrete wavelet transform (DT-CDWT), uses not only the spatial domain but also the frequency domains. Our approach relies on the sharpness, 1-norm estimation in the DT-CDWT domains, and 1-norm estimation in bit-planes in the spatial domain. We describe our image quality assessment method in detail and present experimental results demonstrating its effectiveness.英語フィールド
Author：HAJIME OMURA, TERUYA MINAMOTOTitle：IMAGE QUALITY DEGRADATION ASSESSMENT BASED ON THE DUAL-TREE COMPLEX DISCRETE WAVELET TRANSFORM FOR EVALUATING DIGITAL IMAGEWATERMARKINGAnnouncement information:Proceedings of the 2016 International Conference on Wavelet Analysis and Pattern Recognition Page: pp.270-275An abstract：We propose a new image quality degradation assessment method for evaluating the quality of watermarked images based on the dual-tree complex discrete wavelet transform (DT-CDWT). The peak signal to noise ratio (PSNR) and structural similarity (SSIM) are widely used to evaluate image quality degradation resulting from embedding a digital watermark. However, they do not always correctly evaluate the image quality degradation in such cases since they use only the spatial domain. In contrast, our method, based on the dual-tree complex discrete wavelet transform (DT-CDWT), uses not only the spatial domain but also the frequency domains. Our approach relies on the sharpness, 1-norm estimation in the DT-CDWT domains, and 1-norm estimation in bit-planes in the spatial domain. We describe our image quality assessment method in detail and present experimental results demonstrating its effectiveness.