Novel Recoverable Audio Mosaic Technique Using Segmental and Hierarchical Permutations
Document Type
Article
Publication Date
2-1-2024
Abstract
Mosaic is a prevalent signal-processing approach to hide or protect critical information from users. The conventional mosaic schemes simply abolish or add artificial noise to the original signal content a sender wants to conceal. Thus, they are not recoverable simply by use of a key which can be represented as a very short sequence compared to the concealed signal content. In this work, we extend our previous effort in recoverable image mosaicing to design a novel audio mosaicing approach using hierarchical permutations. Besides, we establish the mathematical relationship between the popular signal-quality metric, namely, signal-to-noise ratio (SNR), and our previously proposed signal-destructuring metric, namely, Kullback-Leibler divergence of discrete cosine transform (DCT-KLD), so that the mosaicing or signal-destructuring effect in terms of DCT-KLD and the general signal-quality measure in terms of SNR can be translated into each other. As a result, one can easily judge if the mosaicked signal reaches the concealability which is equivalent to the maximum SNR to eliminate the intelligibility of an utterance. The new relationship between DCT-KLD and SNR we develop can thus be very useful to qualify an audio mosaic method without any need of human listening test.
Publication Source (Journal or Book title)
IEEE Internet of Things Journal
First Page
4857
Last Page
4871
Recommended Citation
Tsai, M., Huang, S., & Wu, H. (2024). Novel Recoverable Audio Mosaic Technique Using Segmental and Hierarchical Permutations. IEEE Internet of Things Journal, 11 (3), 4857-4871. https://doi.org/10.1109/JIOT.2023.3301333