Investigation of Lossless Audio Compression using IEEE 1857.2 Advanced Audio Coding

2017 ◽  
Vol 6 (2) ◽  
pp. 422
Author(s):  
Teddy Surya Gunawan ◽  
Muhammad Khalif Mat Zain ◽  
Fathiah Abdul Muin ◽  
Mira Kartiwi
Keyword(s):  
Lossless Compression ◽  
Audio Coding ◽  
Audio Compression ◽  
Source File ◽  
Compression Performance ◽  
Audio Quality ◽  
Current State ◽  
Ieee Standard ◽  
Audio Files ◽  
Advanced Audio Coding

<p>Audio compression is a method of reducing the space demand and aid transmission of the source file which then can be categorized by lossy and lossless compression. Lossless audio compression was considered to be a luxury previously due to the limited storage space. However, as storage technology progresses, lossless audio files can be seen as the only plausible choice for those seeking the ultimate audio quality experience. There are a lot of commonly used lossless codecs are FLAC, Wavpack, ALAC, Monkey Audio, True Audio, etc. The IEEE Standard for Advanced Audio Coding (IEEE 1857.2) is a new standard approved by IEEE in 2013 that covers both lossy and lossless audio compression tools. A lot of research has been done on this standard, but this paper will focus more on whether the IEEE 1857.2 lossless audio codec to be a viable alternative to other existing codecs in its current state. Therefore, the objective of this paper is to investigate the codec’s operation as initial measurements performed by researchers show that the lossless compression performance of the IEEE compressor is better than any traditional encoders, while the encoding speed is slower which can be further optimized.</p>

scholarly journals Performance Evaluation of Multichannel Audio Compression

2018 ◽  
Vol 10 (1) ◽  
pp. 146
Author(s):  
Teddy Surya Gunawan ◽  
Mira Kartiwi
Keyword(s):  
Performance Evaluation ◽  
Performance Metrics ◽  
Lossless Compression ◽  
Audio Signals ◽  
Audio Quality ◽  
Multichannel Audio ◽  
Performance Metric ◽  
Audio Files ◽  
Channel Configuration ◽  
Integrated Performance

<p>In recent years, multichannel audio systems are widely used in modern sound devices as it can provide more realistic and engaging experience to the listener. This paper focuses on the performance evaluation of three lossy, i.e. AAC, Ogg Vorbis, and Opus, and three lossless compression, i.e. FLAC, TrueAudio, and WavPack, for multichannel audio signals, including stereo, 5.1 and 7.1 channels. Experiments were conducted on the same three audio files but with different channel configurations. The performance of each encoder was evaluated based on its encoding time (averaged over 100 times), data reduction, and audio quality. Usually, there is always a trade-off between the three metrics. To simplify the evaluation, a new integrated performance metric was proposed that combines all the three performance metrics. Using the new measure, FLAC was found to be the best lossless compression, while Ogg Vorbis and Opus were found to be the best for lossy compression depends on the channel configuration. This result could be used in determining the proper audio format for multichannel audio systems.</p>

scholarly journals Efficient Lossless Compression of Multitemporal Hyperspectral Image Data

2018 ◽  
Vol 4 (12) ◽  
pp. 142 ◽  
Author(s):  
Hongda Shen ◽  
Zhuocheng Jiang ◽  
W. Pan
Keyword(s):  
Data Compression ◽  
Hyperspectral Image ◽  
Image Data ◽  
Lossless Compression ◽  
Large Data ◽  
Hyperspectral Data ◽  
Compression Performance ◽  
Temporal Correlations ◽  
Sensing Applications ◽  
Data Volume

Hyperspectral imaging (HSI) technology has been used for various remote sensing applications due to its excellent capability of monitoring regions-of-interest over a period of time. However, the large data volume of four-dimensional multitemporal hyperspectral imagery demands massive data compression techniques. While conventional 3D hyperspectral data compression methods exploit only spatial and spectral correlations, we propose a simple yet effective predictive lossless compression algorithm that can achieve significant gains on compression efficiency, by also taking into account temporal correlations inherent in the multitemporal data. We present an information theoretic analysis to estimate potential compression performance gain with varying configurations of context vectors. Extensive simulation results demonstrate the effectiveness of the proposed algorithm. We also provide in-depth discussions on how to construct the context vectors in the prediction model for both multitemporal HSI and conventional 3D HSI data.

scholarly journals Improved high-quality MPEG-2/4 advanced audio coding encoder

2008 ◽  
Vol 29 (6) ◽  
pp. 362-371
Author(s):  
Yotaro Kubo ◽  
Masaaki Honda ◽  
Katsuhiko Shirai ◽  
Tomoyasu Komori ◽  
Nobumasa Seiyama ◽  
...  
Keyword(s):  
Audio Coding ◽  
High Quality ◽  
Advanced Audio Coding

scholarly journals Evaluation of Audio Compression Artifacts

10.14311/906 ◽  
2007 ◽  
Vol 47 (1) ◽  
Author(s):  
M. Herrera Martinez
Keyword(s):  
State Of The Art ◽  
Subjective Evaluation ◽  
Audio Coding ◽  
Coding System ◽  
Audio Compression ◽  
Coding Systems ◽  
Wide Range ◽  
Different Types ◽  
Processing Techniques ◽  
Signal Processing Techniques

This paper deals with subjective evaluation of audio-coding systems. From this evaluation, it is found that, depending on the type of signal and the algorithm of the audio-coding system, different types of audible errors arise. These errors are called coding artifacts. Although three kinds of artifacts are perceivable in the auditory domain, the author proposes that in the coding domain there is only one common cause for the appearance of the artifact, inefficient tracking of transient-stochastic signals. For this purpose, state-of-the art audio coding systems use a wide range of signal processing techniques, including application of the wavelet transform, which is described here. 

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