547 research outputs found
Compression using Wavelet Transform
Audio compression has become one of the basic technologies of the multimedia
age. The change in the telecommunication infrastructure, in recent years, from
circuit switched to packet switched systems has also reflected on the way that
speech and audio signals are carried in present systems. In many applications,
such as the design of multimedia workstations and high quality audio
transmission and storage, the goal is to achieve transparent coding of audio and
speech signals at the lowest possible data rates. In other words, bandwidth cost
money, therefore, the transmission and storage of information becomes costly.
However, if we can use less data, both transmission and storage become
cheaper. Further reduction in bit rate is an attractive proposition in applications
like remote broadcast lines, studio links, satellite transmission of high quality
audio and voice over internet
Spread spectrum-based video watermarking algorithms for copyright protection
Merged with duplicate record 10026.1/2263 on 14.03.2017 by CS (TIS)Digital technologies know an unprecedented expansion in the last years. The consumer can
now benefit from hardware and software which was considered state-of-the-art several years
ago. The advantages offered by the digital technologies are major but the same digital
technology opens the door for unlimited piracy. Copying an analogue VCR tape was certainly
possible and relatively easy, in spite of various forms of protection, but due to the analogue
environment, the subsequent copies had an inherent loss in quality. This was a natural way of
limiting the multiple copying of a video material. With digital technology, this barrier
disappears, being possible to make as many copies as desired, without any loss in quality
whatsoever. Digital watermarking is one of the best available tools for fighting this threat.
The aim of the present work was to develop a digital watermarking system compliant with the
recommendations drawn by the EBU, for video broadcast monitoring. Since the watermark
can be inserted in either spatial domain or transform domain, this aspect was investigated and
led to the conclusion that wavelet transform is one of the best solutions available. Since
watermarking is not an easy task, especially considering the robustness under various attacks
several techniques were employed in order to increase the capacity/robustness of the system:
spread-spectrum and modulation techniques to cast the watermark, powerful error correction
to protect the mark, human visual models to insert a robust mark and to ensure its invisibility.
The combination of these methods led to a major improvement, but yet the system wasn't
robust to several important geometrical attacks. In order to achieve this last milestone, the
system uses two distinct watermarks: a spatial domain reference watermark and the main
watermark embedded in the wavelet domain. By using this reference watermark and techniques
specific to image registration, the system is able to determine the parameters of the attack and
revert it. Once the attack was reverted, the main watermark is recovered. The final result is a
high capacity, blind DWr-based video watermarking system, robust to a wide range of attacks.BBC Research & Developmen
Wavelet-Based Audio Embedding & Audio/Video Compression
With the decline in military spending, the United States relies heavily on state side support. Communications has never been more important. High-quality audio and video capabilities are a must. Watermarking, traditionally used for copyright protection, is used in a new and exciting way. An efficient wavelet-based watermarking technique embeds audio information into a video signal. Several highly effective compression techniques are applied to compress the resulting audio/video signal in an embedded fashion. This wavelet-based compression algorithm incorporates bit plane coding, first difference coding, and Huffman coding. To demonstrate the potential of this audio embedding audio/video compression system, an audio signal is embedded into a video signal and the combined signal is compressed. Results show that overall compression rates of 15:1 can be achieved. The video signal is reconstructed with a median PSNR of nearly 33dB. Finally, the audio signal is extracted with out error
Watermarking via zero assigned filter banks
Cataloged from PDF version of article.In order to identify the owner and distributor of digital data, a watermarking scheme in
frequency domain for multimedia files is proposed. The scheme satisfies the
imperceptibility and persistence requirements and it is robust against additive noise.
It consists of a few stages of wavelet decomposition of several subblocks of the original
signal using special zero assigned filter banks. By assigning zeros to filters on the high
frequency portion of the spectrum, filter banks with frequency selective response are
obtained. The information is then inserted in the wavelet-decomposed and compressed
signal. Several robustness tests are performed on male voice, female voice, and music
files, color and gray level images. The algorithm is tested under white Gaussian noise
and against JPEG compression and it is observed to be robust even when exposed to high
levels of corruption.
& 2009 Elsevier B.V. All rights reserve
Adaptive Variable Degree-k Zero-Trees for Re-Encoding of Perceptually Quantized Wavelet-Packet Transformed Audio and High Quality Speech
A fast, efficient and scalable algorithm is proposed, in this paper, for
re-encoding of perceptually quantized wavelet-packet transform (WPT)
coefficients of audio and high quality speech and is called "adaptive variable
degree-k zero-trees" (AVDZ). The quantization process is carried out by taking
into account some basic perceptual considerations, and achieves good subjective
quality with low complexity. The performance of the proposed AVDZ algorithm is
compared with two other zero-tree-based schemes comprising: 1- Embedded
Zero-tree Wavelet (EZW) and 2- The set partitioning in hierarchical trees
(SPIHT). Since EZW and SPIHT are designed for image compression, some
modifications are incorporated in these schemes for their better matching to
audio signals. It is shown that the proposed modifications can improve their
performance by about 15-25%. Furthermore, it is concluded that the proposed
AVDZ algorithm outperforms these modified versions in terms of both output
average bit-rates and computation times.Comment: 30 pages (Double space), 15 figures, 5 tables, ISRN Signal Processing
(in Press
Scalable and perceptual audio compression
This thesis deals with scalable perceptual audio compression. Two scalable perceptual solutions as well as a scalable to lossless solution are proposed and investigated. One of the scalable perceptual solutions is built around sinusoidal modelling of the audio signal whilst the other is built on a transform coding paradigm. The scalable coders are shown to scale both in a waveform matching manner as well as a psychoacoustic manner. In order to measure the psychoacoustic scalability of the systems investigated in this thesis, the similarity between the original signal\u27s psychoacoustic parameters and that of the synthesized signal are compared. The psychoacoustic parameters used are loudness, sharpness, tonahty and roughness. This analysis technique is a novel method used in this thesis and it allows an insight into the perceptual distortion that has been introduced by any coder analyzed in this manner
Wavelet Filter Banks in Perceptual Audio Coding
This thesis studies the application of the wavelet filter bank (WFB) in perceptual audio coding by providing brief overviews of perceptual coding, psychoacoustics, wavelet theory, and existing wavelet coding algorithms. Furthermore, it describes the poor frequency localization property of the WFB and explores one filter design method, in particular, for improving channel separation between the wavelet bands. A wavelet audio coder has also been developed by the author to test the new filters. Preliminary tests indicate that the new filters provide some improvement over other wavelet filters when coding audio signals that are stationary-like and contain only a few harmonic components, and similar results for other types of audio signals that contain many spectral and temporal components.
It has been found that the WFB provides a flexible decomposition scheme through the choice of the tree structure and basis filter, but at the cost of poor localization properties. This flexibility can be a benefit in the context of audio coding but the poor localization properties represent a drawback. Determining ways to fully utilize this flexibility, while minimizing the effects of poor time-frequency localization, is an area that is still very much open for research
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