Audio compression using transforms and high order entropy encoding

Abstract

<span>Digital audio is required to transmit large sizes of audio information through the most common communication systems; in turn this leads to more challenges in both storage and archieving. In this paper, an efficient audio compressive scheme is proposed, it depends on combined transform coding scheme; it is consist of i) bi-orthogonal (tab 9/7) wavelet transform to decompose the audio signal into low & multi high sub-bands, ii) then the produced sub-bands passed through DCT to de-correlate the signal, iii) the product of the combined transform stage is passed through progressive hierarchical quantization, then traditional run-length encoding (RLE), iv) and finally LZW coding to generate the output mate bitstream. The measures Peak signal-to-noise ratio (PSNR) and compression ratio (CR) were used to conduct a comparative analysis for the performance of the whole system. Many audio test samples were utilized to test the performance behavior; the used samples have various sizes and vary in features. The simulation results appear the efficiency of these combined transforms when using LZW within the domain of data compression. The compression results are encouraging and show a remarkable reduction in audio file size with good fidelity.</span>

A Survey paper on Lossy Audio Compression Methods

“…The results presented in table below showed that the compression technique in [25] achieved better results for the selected sample.…”

“…Zainab and et al presents a technique depends on combine transforms (wavelet transform and DCT) coding scheme, to decompose the signal into low and multi high sub bands, bi-orthogonal (tab 9/7) wavelet transform was used then DCT was used to de-correlate the sub-bands then quantization (progressive hierarchical) applied followed by Run Length Encoding and finally LZW was applied to generate the compressed stream [25].…”

“…It is possible to include the results for the methods used by the authors in their previous work and for the same sample. An audio test sample is used to compare between two techniques of compression method which used previously in two papers [15,25], the characteristics of the audio test sample are presented in the table below:…”

Speech Coding Using Discrete Cosine Transform and Chaotic Map

“…A group of consecutive data is quantized to a data group of discrete values. The primary purpose is to reduce the amount of data in threshold coefficients [8].…”

Adaptive speech compression based on AMBTC

“…Consequently, we can achieve high compression ratios with acceptable SNR. The resulting signal comparison is done with the SNR, the NRMSE, and the signal-tonoise ratio (PSNR) [12,13]. Smita et al, have applied various speech compression techniques, where the signal is converted to a compressed or compressed form.…”