Modified Discrete Cosine Transform Domain Research Articles

A Psychoacoustic-Based Multiple Audio Object Coding Approach via Intra-Object Sparsity

Rendering spatial sound scenes via audio objects has become popular in recent years, since it can provide more flexibility for different auditory scenarios, such as 3D movies, spatial audio communication and virtual classrooms. To facilitate high-quality bitrate-efficient distribution for spatial audio objects, an encoding scheme based on intra-object sparsity (approximate k-sparsity of the audio object itself) is proposed in this paper. The statistical analysis is presented to validate the notion that the audio object has a stronger sparseness in the Modified Discrete Cosine Transform (MDCT) domain than in the Short Time Fourier Transform (STFT) domain. By exploiting intra-object sparsity in the MDCT domain, multiple simultaneously occurring audio objects are compressed into a mono downmix signal with side information. To ensure a balanced perception quality of audio objects, a Psychoacoustic-based time-frequency instants sorting algorithm and an energy equalized Number of Preserved Time-Frequency Bins (NPTF) allocation strategy are proposed, which are employed in the underlying compression framework. The downmix signal can be further encoded via Scalar Quantized Vector Huffman Coding (SQVH) technique at a desirable bitrate, and the side information is transmitted in a lossless manner. Both objective and subjective evaluations show that the proposed encoding scheme outperforms the Sparsity Analysis (SPA) approach and Spatial Audio Object Coding (SAOC) in cases where eight objects were jointly encoded.

An MDCT domain three-point interpolation-based low-complexity frequency estimator

Signal frequency estimation is a problem of significance in many applications including audio signal processing. Compressed domain audio frequency estimators that directly use the modified discrete cosine transform (MDCT) coefficients are suitable for low-complexity audio applications. A new frequency estimation approach, which can obtain the estimated value from a simple combination of three MDCT coefficients, is proposed herein. It exploits the underlying relation among adjacent MDCT values and provides a general form of this type of estimators. The estimator manifests obvious computational advantages over other MDCT domain estimators and is suitable for high signal-to-noise ratio (SNR) conditions.

A Robust Audio Watermarking Technique Operates in MDCT Domain based on Perceptual Measures

the review presents a digital audio watermarking technique operating in the frequency domain with two variants. This technique uses the Modified Discrete Cosine Transform (MDCT) to move to the frequency domain. To ensure more inaudibility, we exploited the proprieties of the psychoacoustic model 1 (PMH1) of MPEG1 encoder layer I in the first variant and those of psychoacoustic model 2 (PMH2) of MPEG1 encoder Layer III in the second alternative to search the places for insertion of the watermark. In both variants of the technique, the bits of the mark will be duplicated to increase the capacity of insertion then inserted into the least significant bit (LSB). For more reliability in the detection phase, we use an error correction code (Hamming) on the mark. Next, to analyze the performance of the proposed technique, we perform two comparative studies. In the first, we compare the proposed digital audio watermarking technique with her two variants and those achieved by Luigi Rosa and Rolf Brigola, ‘which we download the M-files of each’. The technique developed by Luigi Rosa operates in the frequency domain but using the Discrete Cosine Transform (DCT) as transformation and that proposed by Rolf Brigola uses the Fast Fourier Transform (FFT). We studied the robustness of each technique against different types of attacks such as compression / decompression MP3, stirmark audio attack and we evaluated the inaudibility by using an objective approach by calculating the SNR and the ODG notes given by PEAQ. The robustness of this technique is shown against different types of attacks. In the second, we prove the contribution of the proposed technique by comparing the payload data, imperceptibility and robustness against attack MP3 with others existing techniques in the literature

MDCT Sinusoidal Analysis for Audio Signals Analysis and Processing

The Modified Discrete Cosine Transform (MDCT) is widely used in audio signals compression, but mostly limited to representing audio signals. This is because the MDCT is a real transform: Phase information is missing and spectral power varies frame to frame even for pure sine waves. We have a key observation concerning the structure of the MDCT spectrum of a sine wave: Across frames, the complete spectrum changes substantially, but if separated into even and odd subspectra, neither changes except scaling. Inspired by this observation, we find that the MDCT spectrum of a sine wave can be represented as an envelope factor times a phase-modulation factor. The first one is shift-invariant and depends only on the sine wave's amplitude and frequency, thus stays constant over frames. The second one has the form of sinθ for all odd bins and cosθ for all even bins, leading to subspectra's constant shapes. But this θ depends on the start point of a transform frame, therefore, changes at each new frame, and then changes the whole spectrum. We apply this formulation of the MDCT spectral structure to frequency estimation in the MDCT domain, both for pure sine waves and sine waves with noises. Compared to existing methods, ours are more accurate and more general (not limited to the sine window). We also apply the spectral structure to stereo coding. A pure tone or tone-dominant stereo signal may have very different left and right MDCT spectra, but their subspectra have similar shapes. One ratio for even bins and one ratio for odd bins will be enough to reconstruct the right from the left, saving half bitrate. This scheme is simple and at the same time more efficient than the traditional Intensity Stereo (IS).

Transform Coding Based on Source Filter Model in the MDCT Domain

State-of-the-art voice codecs have been developed to extend the input bandwidth to enhance quality while maintaining interoperability with a legacy codec. Most of them employ a modified discrete cosine transform (MDCT) for coding their extended band. We propose a source filter model-based coding algorithm of MDCT spectral coefficients, apply it to the ITU-T G.711.1 super wideband (SWB) extension codec, and subjectively test it to validate the model. A subjective test shows a better quality over the standardized SWB codec.

DFT spectrum estimation from critically sampled lapped transforms

Critically sampled perfect reconstruction lapped transforms (LT), apart from signal representation, are difficult to use for signal analysis and processing. We tackle this problem by establishing a novel connection between the LT and the DFT based on matrix analysis. Specifically, for the modified discrete cosine transform (MDCT) with an arbitrary symmetric window, one of the most widely used LT, a sparse matrix representation for the conversion to and from the DFT is developed, leading to an efficient implementation in the form of low-order frequency domain FIR filtering. We give two example applications, MDCT domain group delay estimation and aliasing reduction for the temporal noise shaping (TNS).

Streaming audio packet loss concealment based on sinusoidal frequency estimation in MDCT domain

A Packet Loss Concealment (PLC) method is proposed for audio streaming represented in the Modified Discrete Cosine Transform (MDCT) domain. MDCT is the dominant transform of perceptual audio coding and widely used in consumer electronics. The MDCT coefficients of a lost frame are reconstructed by our PLC method, which is based on audio sinusoidal model in MDCT domain. The sinusoid-like coefficients could be predicted by sinusoidal frequency estimation, and further optimization of computation is achieved by using sign property of sinusoids. In order to compare with other approaches, both subjective and objective evaluation tests are conducted. The experimental results show that the computational complexity and memory requirement of our approach are greatly reduced, while good quality is maintained.

Spatial parameters for audio coding: MDCT domain analysis and synthesis

We use Modified Discrete Cosine Transform (MDCT) to analyze and synthesize spatial parameters. MDCT in itself lacks phase information and energy conservation, which are needed by spatial parameters representation. Completing MDCT with Modified Discrete Sine Transform (MDST) into "MDCT-j*MDST" overcomes this and enables the representation in a form similar to that of DFT. And due to overlap-add in time domain, a MDST spectrum can be built perfectly from MDCT spectra of neighboring frames through matrix-vector multiplication. The matrix is heavily diagonal and keeping only a small number of its sub-diagonals is sufficient for approximation. When using MDCT based core coder in spatial audio coding, like Advanced Audio Coding (AAC), we need no separate transforming for spatial processing, cutting down significantly the computational complexity. Subjective listening tests also show that MDCT domain spatial processing has no quality impairment.

An accurate low complexity algorithm for frequency estimation in MDCT domain

This paper addresses the extraction of frequency, amplitude, and phase of sinusoidal components directly from modified discrete cosine transform (MDCT) domain, which is broadly used in many digital audio applications. An efficient method is proposed for portable device based on the approximation of MDCT expression and the simple combinations of local maximum MDCT coefficients. By extracting the frequency and amplitude of a stationary sinusoid, the experimental results demonstrate that the proposed algorithm produces accurate results with low computational complexity.