On perceptual distortion measures and parametric modeling

Perceptual Significance of Cepstral Distortion Measures in Digital Speech Processing

Currently, one of the most widely used distance measures in speech and speaker recognition is the Euclidean distance between mel frequency cepstral coefficients (MFCC). MFCCs are based on filter bank algorithm whose filters are equally spaced on a perceptually motivated mel frequency scale. The value of mel cepstral vector, as well as the properties of the corresponding cepstral distance, are d...

Perceptual Image Distortion

In this paper we present a perceptual distortion mea sure that predicts image integrity far better than mean squared error This perceptual distortion measure is based on a model of human visual processing that ts empirical measurements of the psychophysics of spatial pattern de tection The model of human visual processing proposed involves two major components a steerable pyramid trans form and...

Effect of noise and distortion in speech on parametric extraction

Sampling Distortion Measures

This paper is motivated by the following problem. Consider an image we want to compress. The appropriate distortion measure with respect to which we compress the image is specified by the human visual system. This distortion measure can only be experimentally determined and our knowledge about it will hence be only partial. This leads us to consider the general problem of lossy source coding wi...

On Optimal Reinsurance Policy with Distortion Risk Measures and Premiums

In this paper, we consider the problem of optimal reinsurance design, when the risk is measured by a distortion risk measure and the premium is given by a distortion risk premium. First, we show how the optimal reinsurance design for the ceding company, the reinsurance company and the social planner can be formulated in the same way. Second, by introducing the “marginal indemnification function...