Tejaswi Nanjundaswamy

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Conventional “pixel copying” prediction used in current video standards was shown in previous work to be sub-optimal compared to 2-D non-separable Markov model based recursive extrapolation approaches. The premise of this paper is that in order to achieve the full potential of these approaches it is necessary to account for several(More)
This paper focuses on a new framework for scalable coding of information based on principles derived from common information of two dependent random variables. In the conventional successive refinement setting, the encoder generates two layers of information called the base layer and the enhancement layer. The first decoder, which receives only the base(More)
The long term prediction (LTP) tool is used in audio compression systems to exploit periodicity in signals. This tool capitalizes on the periodic component of the waveform by selecting a past segment as the basis for prediction of the current frame. However, most audio signals are polyphonic in nature, consisting of a mixture of periodic signals. This(More)
Current video coders exploit temporal dependencies via prediction that consists of motion-compensated pixel copying operations. Such per-pixel temporal prediction ignores important underlying spatial correlations, as well as considerable variations in temporal correlation across frequency components. In the transform domain, however, spatial decorrelation(More)
A novel filtering approach that naturally combines information from both intra-frame and motion compensated refer-encing for efficient prediction is proposed to fully exploit the spatio-temporal correlations of video signals, thereby achieving superior compression performance. Inspiration was drawn from our recent work on extrapolation filter based intra(More)
MPEG-4 High-Definition Advanced Audio Coding (HD-AAC) enables scalable-to-lossless (SLS) audio coding with an Advanced Audio Coding (AAC) base layer, and fine-grained enhancements based on the MPEG SLS standard. While the AAC core offers better perceptual quality at lossy bit-rates, its inclusion has been observed to compromise the ultimate lossless(More)
Current scalable audio coders typically optimize performance at a particular layer without regard to impact on other layers, and are thus unable to provide a performance trade-off between different layers. In the particular case of MPEG Scalable Advanced Audio Coding (S-AAC) and Scalable-to-Lossless (SLS) coding, the base-layer is optimized first followed(More)
This paper proposes a frame loss concealment technique for audio signals, which is designed to overcome the main challenge due to the polyphonic nature of most music signals and is inspired by our recent research on compression of such signals. The underlying idea is to employ a cascade of long term prediction filters (tailored to the periodic components)(More)
Scalable coders generate hierarchically layered bitstreams to serve content at different quality levels, wherein the base layer provides a coarse quality reconstruction and successive layers incrementally refine the quality. However, it is widely recognized that there is an inherent performance penalty due to the scalable coding structure, when compared to(More)
Prediction is used in virtually all compression systems. When such a compressed signal is transmitted over unreliable networks, packet losses can lead to significant error propagation through the prediction loop. Despite this, the conventional design technique completely ignores the effect of packet losses, and estimates the prediction parameters to(More)