Statistics of natural and urban images

Ziegaus, Christian; Lang, Elmar

doi:10.1007/bfb0020159

Cited by 7 publications

(1 citation statement)

References 3 publications

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“…Interestingly, all of the aforementioned weighted contrasts are based on fourth-order statistics, which makes them more suitable for symmetric sources than for asymmetric ones. Note that asymmetric sources arise in many practical scenarios, such as in sonar signal processing (Nikias & Petropulu 1993) or source separation of urban images (Ziegaus & Lang 1997), see also Karvanen & Koivunen (2004). In some cases, digitized speech signals have non-zero skewness; separation of such signals obtains some benefit from third-order statistics (Choi et al 1998).…”

Section: J ðYþ Zmentioning

confidence: 99%

Independent component analysis: Jacobi-like diagonalization of optimized composite-order cumulants

Abrar

Nandi

2009

Proc. R. Soc. A.

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In the field of blind source separation, Jacobi-like diagonalization-based approaches constitute an important tool for independent component analysis (ICA). Recently, simultaneous diagonalization of cumulant matrices of third-and fourth-order has been studied by a number of authors. In this work, we present an optimal parametrized composition of these cumulants that puts two classical contrasts, namely, the cumulantbased ICA and the weighted fourth-order contrast in a common framework. It is shown that the optimal weight parameter depends on the a priori statistical knowledge of the original mixing sources. Following the same spirit of the ICA algorithm, we derive the analytical solution for the case of two sources. Finally, a number of computer simulations have been performed to illustrate the behaviour of the Jacobi-like iterations for the maximization of the proposed parametrized contrast.

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Section: J ðYþ Zmentioning

confidence: 99%