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A blind audio watermarking algorithm in the time domain is proposed. The audio signal is divided into frames and the watermark is inserted on a frame by frame basis. The proposed algorithm detects the watermark using a signal processor based on the stochastic resonance mechanism. The watermark detection does not need the original audio. The parameter-induce stochastic resonance in audio watermarking is observed and the interpretation to this phenomenon is given. For the synchronization attack, the experimental results show that the stochastic resonance signal processor can catch up and surpass the performance of the matched filter. This reveals a robustness superiority of the stochastic resonance signal processor, compared to the matched filter operating outside its strict nominal conditions, which is especially helpful for the audio watermarking.

The paper addresses the noise image which adopts the embedded zerotree wavelet coding algorithm to compress and then results in decreasing the amount of the zerotree and increasing the amount of the alone-zero, which will affect the compression effect. Therefore this paper brings forward the characteristic directional median filter to reduce noise before the noise image compression; aim at solving the insufficiency of the scope table order frequent adjusts in the EZW algorithm, we proposes to adopt adaptive depth first search strategy through definition floating threshold. The result shows that the new image compression scheme has improved better than traditional EZW algorithm in the aspects of image quality, compression effect and compression coding efficiency.