In this paper, we develop a higher-order statistical theory of matching models against images. The basic idea is not only to take into account how much of an object can be seen in the image, but also what parts of it are jointly present. We show that this additional information can improve the speciicity (i.e., reduce the probability of false positive matches) of a recognition algorithm. We dem...

| Low rank estimators for higher order statistics are considered in this paper. Rank reduction methods ooer a general principle for trading estimator bias for reduced estimator variance. The bias-variance tradeoo is analyzed for low rank estimators of higher order statistics using a tensor product formulation for the moments and cumulants. In general the low rank estimators have a larger bias a...

Researchers studying human and computer vision have found description and construction of these systems greatly aided by analysis of the statistical properties of naturally occurring scenes. More specifically, it has been found that receptive fields with directional selectivity and bandwidth properties similar to mammalian visual systems are more closely matched to the statistics of natural sce...

The performed job, in this study, consists in studying adaptive filters and higher order statistics (HOS) to ameliorate their performances, by extension of linear case to non linear filters via Volterra series. This study is, principally, axed on:  Choice of the adaptation step and convergence conditions.  Convergence rate.  Adaptive variation of the convergence factor, according to the inpu...

A robust and effective voice activity detection (VAD) algorithm is proposed for improving speech recognition performance in noisy environments. The approach is based on filtering the input channel to avoid high energy noisy components and then the determination of the speech/non-speech bispectra by means of third order autocumulants. This algorithm differs from many others in the way the decisi...

Most of the techniques for image restoration are based on some known degradation models. But in many situations it is difficult to accurately measure the degradation factors or noise type that is the real motivation behind the use of blind deconvolution technique for image restoration. Here the observed degraded image is restored without having any prior knowledge about the noise type. Most of ...

Universal blind steganalysis attempts to detect steganographic data without knowledge about the applied steganographic system. Farid proposed such a detection algorithm based on higher-order statistics for separating original images from stego images. His method shows an astonishing performance on current steganographic schemes. Starting from the statistical approach in Farid’s algorithm, we in...