Novel Recoverable Audio Mosaic Technique Using Segmental and Hierarchical Permutations
Morris C.-H. Tsai, Scott C.-H. Huang, Hsiao‐Chun Wu · IEEE Internet of Things Journal · 2023
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.