Subband coding of audio signal with logarithmic compandors

Perić, Zoran; Tančić, Milan; Tomić, Stefan; Ćirić, Dejan

doi:10.1109/telsks.2015.7357728

Cited by 2 publications

(9 citation statements)

References 3 publications

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“…As these are the theoretical values, we conducted a practical examination of the coding schemes performance for different bit rate combinations. The examination of the non-adaptive SBC scheme was conducted in [12] and it was concluded that the most appropriate bit rate combination for this coding scheme is R 1 =10 and R 2 =8 bits per sample. This deviates from the theoretically obtained combination, and it was experimentally confirmed in [12].…”

Section: The Numerical Results and Analysismentioning

confidence: 99%

“…It has been shown that the Laplacian source can be successfully used to model speech or audio signal [6]. Granular and overload distortion for quasi-logarithmic quantizer designed for Laplacian source of variance σ 2 and mean value equal to zero, can be calculated from [2,12]:…”

Section: Design Of the Sub-band Coding Scheme With A Quasi-logarithmimentioning

confidence: 99%

“…Greater support limit contributes to a bigger granular and smaller overload distortion, and vice versa [2,7,10]. The support limits in the non-adaptive quantization scheme are determined based on the experience from the previous research and by empirical investigation, so that x max1 =10 and x max2 =3 [12]. As mentioned, an objective quality measure used in the analysis is SQNR, defined as [6]:…”

Section: Design Of the Sub-band Coding Scheme With A Quasi-logarithmimentioning

confidence: 99%

“…In this case, the support limit values are designed for the fixed quantizer and Laplacian source. The values of the support limits for the first frame are determined as and [12]. The optimal support limit for the Laplacian source of unit variance is given as [10]:…”

Section: A Sub-band Coding Scheme With the Backward-adaptive Quasi-lomentioning

confidence: 99%

“…Moreover, a compressed signal can be transmitted more efficiently by using fewer resources. Sub-band coding has been widely implemented in audio, still images and video coding [4,12,[15][16]. This technique represents a form of transform coding, which applies certain transformations to the input signal, for achieving more efficient data compression.…”

Section: Introductionmentioning

confidence: 99%

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Backward Adaptive and Quasi-Logarithmic Quantizer for Sub-Band Coding of Audio

Tomić

Perić²,

Tančić³

et al. 2018

ITC

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This research presents an audio coding scheme, based on sub-band coding (SBC), with the implementation of quasi-logarithmic compandors. The presented coding scheme is based on signal decomposition and individual processing of the different sub-bands. Two SBC schemes for audio coding are presented, a non-adaptive and an adaptive coding scheme. The application of backward adaptation technique further improves the performance of this coding scheme, especially when using smaller compression factor values. This paper also describes the determination of an efficient bit allocation, used for coding the individual sub-bands. The results indicate that the proposed coding schemes can successfully be implemented in audio signal coding, providing a high quality output signal.

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Section: The Numerical Results and Analysismentioning

confidence: 99%

Section: Design Of the Sub-band Coding Scheme With A Quasi-logarithmimentioning

confidence: 99%

Section: Design Of the Sub-band Coding Scheme With A Quasi-logarithmimentioning

confidence: 99%

Section: A Sub-band Coding Scheme With the Backward-adaptive Quasi-lomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Backward Adaptive and Quasi-Logarithmic Quantizer for Sub-Band Coding of Audio

Tomić

Perić²,

Tančić³

et al. 2018

ITC

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Speech Signal Coding Using Forward Adaptive Quantization and Simple Transform Coding

Tančić¹,

Perić²,

Tomić³

et al. 2016

ElAEE

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The paper proposes a novel speech signal coding scheme that implements a simple transform coding and forward adaptive quantization. The proposed scheme is adapted to the input signal variance, providing highly efficient bandwidth usage, whereas implemented transform coding provides sub-sequences with more predictable signal characteristics, so that more suitable signal processing can be performed. The aforementioned transform coding precedes adaptive quantization, providing additional compression. The objective quality measure used for system performance estimation is SQNR (signal-to-quantization-noise ratio), which represents a standard measure for lossy coding types. The influence of transform coding is discussed by comparing the obtained results with the corresponding one achieved by applying only the same adaptive quantization. Furthermore, the comparison with system performance of PCM (pulse-code modulation) coding system confirms that the proposed coding scheme has a lot of potential for further implementation, since that the proposed system ensures SQNR gain up to 4.0983 [dB] for various values of system parameters.

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Subband coding of audio signal with logarithmic compandors

Cited by 2 publications

References 3 publications

Backward Adaptive and Quasi-Logarithmic Quantizer for Sub-Band Coding of Audio

Backward Adaptive and Quasi-Logarithmic Quantizer for Sub-Band Coding of Audio

Speech Signal Coding Using Forward Adaptive Quantization and Simple Transform Coding

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