• The Journal of the Acoustical Society of Korea
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• v.30 no.6
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• pp.303-307
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• 2011

This paper describes an audio watermarking using Quantization Index Modulation (QIM) on significant peaks in frequency domain. The audio signal is broken up into L samples length frames with non-overlapping and rectangular window. The zero-crossing rate of each frame is calculated for decision whether it is proper to be watermarked or not. If the frame is legitimate, frequency magnitude response is computed by discrete Fourier transform. For the QIM, we set the quantization step size based on maximum value of frequency magnitude response and select n significant peaks with w samples around them in frequency domain, totally $n{\times}(w+1)$ samples. Finally, watermark embedding is performed. Decoder extract watermarks based on Euclidean distance, that is a blind detection. The proposed method is robust against many attacks of watermark benchmark.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.11C
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• pp.1066-1070
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• 2006

In this paper, we present a residual filter to improve performance of H.264 compressed video. In general, noisy video sequences captured by imaging system result in decline of coding efficiency and unpleasant coding artifacts due to higher frequency components. By incorporating local statistics and quantization parameter into filtering process, the spurious noise is significantly attenuated and coding efficiency is improved, leading to improvement of visual quality and to bit-rate saving for given quantization step size. In addition, in order to reduce the complexity of the residual filter, noise induced by analyzing H.264 transformation and quantization processes are introduced. The simulation results show the capability of the proposed algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2C
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• pp.41-48
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• 2005

In this paper, we present a low complexity modified Gaussian model based pre-processing filter to improve the performance of H.264 compressed video. Video sequence captured by general imaging system represents the degraded version due to the additive noise which decreases coding efficiency and results in unpleasant coding artifacts due to higher frequency components. By incorporating local statistics and quantization parameter into filtering process, the spurious noise is significantly attenuated and coding efficiency is improved for given quantization step size. In addition, in order to reduce the complexity of the pre-processing filter, the simplified local statistics and quantization parameter are introduced. The simulation results show the capability of the proposed algorithm.