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This paper discusses the application of the Set Par- titioning In Hierarchical Trees (SPIHT) algorithm to the compression of audio signals. Simultaneous masking is used to reduce the number of coefficients required for the representation of the audio signal. The proposed scheme is based on the combina- tion of the Modulated Lapped Transform (MLT) a...
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... This correlation can be reduced by using a rate scalable embedded coding technique i.e., Set Partitioning In Hierarchical Trees (SPIHT) algorithm [16], which has become the most used encoding technique for wavelet coefficients [7]. SPIHT builds on the principle that spectral components with more energy content should be transmitted before other components, allowing the most relevant information to be transmitted using the limited bandwidth available [15]. The algorithm sorts the available wavelet coefficients and transmits both the sorted coefficients and sorting information in an embedded bitstream. ...
Digital audio coding delays have become increasingly critical in real-time wireless applications. In live productions, a codec with ultra low delay is required within the constraints of the available channel bandwidth. However, such a threshold can hardly be reached by means of standard audio coding schemes. To achieve low delay as well as to satisfy cost and power consumption constraints, this paper presents an ultra low delay audio coder by very short block processing and embedded coding implemented in fixed-point DSP. The short block two dimensional (2D) spatial-frequency processing of audio input signal fully exploits the correlation for better compression performance. Lifting wavelet transform with boundary effects minimized by changing wavelet shape is developed using bit shifts and additions to replace multiplications in a fixed-point specification under accuracy constraint. The embedded coding offers the error resilience feature so that joint source-channel coding scheme for unequal error protection can be easily designed by varying both source coding bit rate and channel coding redundancy. Experimental results demonstrate that the proposed coder is efficient and requires less memory in fixed-point computation which guarantees no overflow.
... As shown inTable 3(d), relatively better results are obtained with this modification. However, these results are almost the same as those ofTable 2. In some papers SPIHT is integrated, as such, in the audio or speech codec3334353637. While, only in few reported works it is tried to modify and use it for audio or speech coding [28, 38]. ...
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.
... In this case coder deals with one-dimensional input data set (or several data sets for multi-channel audio). Wavelets also introduce some advantages for audio coding and don't yield to MPEG in coding efficiency [5]. commercial chip which provides real-time video compression using wavelet transformation with up to 350 compression ratio for VHS quality video [6]. ...
... Also, The algorithm provide superior quality for partial reconstructed signals. To evaluate the performance of the algorithm, we compare these result with those obtained in [14] as shown in table (4). The proposed algorithm outperform by 10 -27 db (except X4) with less bit rate. ...
In this paper an efficient algorithm proposed to encode the audio signals with multirate capability. The algorithm based on combining discrete wavelet with DCT transform for maximum decorrelation. The coefficients of the frame are scaled and encoded using non uniform quantizer. The main features of this algorithm are: low complexity and near transparent audio quality resulted in the range 48 – 64 Kbps for most SQAM signals. The algorithm outperform much better than DWPT with SPIHT algorithm previously.
... The scalable to lossless scheme presented in [9] is the basis upon which the bandwidth scalable coder is built, as such it will be described first.Figure 1 illustrates the PSPIHT scalable to lossless scheme. It consists of the combination of the lossy coder presented in [11], which is based on the Modulated Lapped Transform (MLT) and SPIHT, and a lossless coder for transmitting the error incurred from the lossy part. The lossy part is given by the right half of the structure inFig. ...
This paper extends a scalable to lossless compression scheme to allow scalability in terms of sampling rate as well as quantization resolution. The scheme presented is an extension of a perceptu- ally scalable scheme that scales to lossless compression, producing smooth objective scalability, in terms of SNR, until lossless com- pression is achieved. The scheme is built around the Perceptual SPIHT algorithm, which is a modification of the SPIHT algorithm. An analysis of the expected limitations of scaling across sampling rates is given as well as lossless compression results showing the competitive performance of the presented technique.
... The structure of the coder proposed in this paper is depicted inFigure 1. It consists of the combination of the lossy coder of [11], which is based on the Modulated Lapped Transform (MLT) and SPIHT, and a lossless coder for transmitting the error made by the lossy part. The lossy part is given by the right half of the structure inFigure 1, and the error coding (if present) takes place in the left half. ...
... If a set becomes significant with regard to the tested bitplane, it gets partitioned into smaller sets which will be tested for significance again, until all significant coefficients are localized. In this paper, as in [11], the offspring of coefficient are defined by ...
This paper discusses the design and implementation of a scalable audio compression scheme that scales up from lossy to lossless compression. Scalable audio compression has been of interest in the audio compression community for some time, with the most obvious attempt at obtaining a solution coming in the form of the MPEG-4 standard [1]. At the same time the increase in bit rates in both mobile communications [2] and the internet's broadband technology means that audio compression algorithms with higher bit rates than currently used, such as MPEG's mp3 [1], can be employed to obtain higher quality. However, the new increased data rates are not necessarily constant, this is especially the case when considering the internet. As such, scalable schemes that can scale to lossless compression have become rather interesting from an application point of view. The scheme presented in this paper achieves lossless compression that is comparable with the state of the art whilst maintaining a scalable embedded bitstream.
De plus en plus, les images médicales sont acquises et stockées digitalement. Ces images peuvent être très grandes en nombre et en dimension. La compression offre à un moyen de réduire le coût de stockage et augmenter la vitesse de transmission sans une altération flagrante de la qualité de l'image. Une compression avec perte permet d'obtenir une haute compression cependant la communauté médicale favorise une compression sans perte pour des raisons cliniques. Dans ce contexte, ce papier présente une approche de compression adaptative basée sur des codeurs imbriqués et destinée à appliquer les deux modes de compression : avec et sans perte. Il s'agit d'une hybridation d'une Transformée réversible RDCT avec le codeur EZW modifié pour un codage sans perte la région d'intérêt tandis que l'arrière plan est compressé avec perte. Testé sur des images IRM du cerveau, l'algorithme proposé montre son efficacité et sa performance en termes de taux de compression et conservation de l'information nécessaire au diagnostic.
The paper proposes a technique for scalable to lossless audio compression. The scheme presented is perceptually scalable and also provides for lossless compression. It produces smooth objective scalability, in terms of SegSNR, from lossy to lossless compression. The proposal is built around the introduced perceptual SPIHT algorithm, which is a modification of the SPIHT algorithm. Both objective and subjective results are reported and demonstrate both perceptual and objective measure scalability. The subjective results indicate that the proposed method performs comparably with the MPEG-4 AAC coder at 16, 32 and 64 kbps, yet also achieves a scalable-to-lossless architecture.
The possibility of broadcasting television signal real-time transmission over cellular networks has been studied. The results of experimental investigation of discrete cosine and wavelet based video and audio compression techniques efficiencies have been compared. It was shown that wavelet based compression algorithms allow achieving the necessary compression ratios while conserving sufficient video and audio quality for bandwidth limited cellular networks transmission.
Wireless systems are often subject to the constraints of the available channel bandwidth. The key enabling technology for digital wireless products is audio compression. For real time wireless transmission, very low encoding and decoding delay has become an essential prerequisite. In live productions, the tolerable total delay time is less than a few milliseconds. Current audio coding schemes like MPEG standards or wavelet technique can hardly reach such a threshold by using overlapping frames of input signal with psychoacoustic model. This paper presents a new wavelet audio coder with ultra low delay for real time wireless transmission using non-overlapping short block processing and embedded coding. Two dimensional (2D) fast lifting wavelet transform with boundary effects minimized is developed for further exploring the correlation of the audio signal. A modified 2D SPIHT (set partitioning in hierarchical trees) algorithm with more bits used to encode the wavelet coefficients, is implemented to reduce the correlation between the coefficients at different decomposition levels and inside each band at scalable bit rates. Experimental tests demonstrate that the proposed coder is efficient and has low complexity with less memory requirements in implementation.
