Multi-rate and multi-resolution scalable to lossless audio compression using PSPIHT

This paper presents a scalable to lossless compression scheme that allows scalability in terms of sampling rate as well as quantization resolution. The scheme presented is perceptually scalable and it also allows lossless compression. The scheme produces smooth objective scalability, in terms of SNR, until lossless compression is achieved. The scheme is built around the perceptual SPIHT algorithm, which is a modification of the SPIHT algorithm. Objective and subjective results are given that show perceptual as well as objective scalability. The subjective results given also show that the proposed scheme performs comparably with the MPEG-4 AAC coder at 16, 32 and 64 kbps

Scalable and perceptual audio compression

This thesis deals with scalable perceptual audio compression. Two scalable perceptual solutions as well as a scalable to lossless solution are proposed and investigated. One of the scalable perceptual solutions is built around sinusoidal modelling of the audio signal whilst the other is built on a transform coding paradigm. The scalable coders are shown to scale both in a waveform matching manner as well as a psychoacoustic manner. In order to measure the psychoacoustic scalability of the systems investigated in this thesis, the similarity between the original signal\u27s psychoacoustic parameters and that of the synthesized signal are compared. The psychoacoustic parameters used are loudness, sharpness, tonahty and roughness. This analysis technique is a novel method used in this thesis and it allows an insight into the perceptual distortion that has been introduced by any coder analyzed in this manner