@inproceedings{53a93d3ce5524602bdd6f48ad469cad1,
title = "The design and application of DWT-domain optimum decoders",
abstract = "Based on Bayes theory of hypothesis testing, a new DWT-domain decoder structure for image watermarking has been proposed in this work. The statistical distribution of wavelet coefficients is deliberately described with the Laplacian model so that the decoding algorithm could couple effectiveness and simplicity. Under the Neyman-Pearson criterion, the decision rule is optimized by minimizing the probability of missing the watermark for a given false detection rate. Compared with other domain decoders, the proposed DWT-domain decoder has more flexibility in constructing new watermarking algorithms by using visual models that have varying spatial support.",
author = "Yongjian HU and Sam KWONG and CHAN, {Y. K.}",
year = "2003",
doi = "10.1007/3-540-36617-2_3",
language = "English",
isbn = "9783540012177",
series = "Lecture Notes in Computer Science",
publisher = "Springer Berlin",
pages = "22--30",
editor = "KIM, {Hyoung Joong}",
booktitle = "Digital Watermarking: First International Workshop, IWDW 2002, Seoul, Korea, November 21-22, 2002, Revised Papers",
address = "Germany",
note = "International Workshop on Digital Watermarking 2022, IWDW 2002 ; Conference date: 21-11-2002 Through 22-11-2002",
}