Joint binary image deconvolution and blur identification in the context of two-dimensional storage channels - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue Signal Processing Année : 2011

Joint binary image deconvolution and blur identification in the context of two-dimensional storage channels

Résumé

We consider blurring of binary images and corruption by ambient noise occuring on two-dimensional storage channels. Since coding is generally used in such systems, the deconvolution problem can be treated jointly with decoding. Several methods have been proposed in the literature under the name of turbo equalization to mitigate the degradation introduced by such channels. However, the problem of blur identification has rarely been addressed previously. In this paper, we propose a technique for estimating the 2D channel coefficients, along with the variance of the ambient noise. The proposed estimation algorithm is adaptive and performed jointly with turbo equalization, so as to limit the number of known pilot symbols needed to bootstrap the channel estimator. Interestingly, we found that the computational complexity of the proposed joint channel estimation and turbo equalization method depends heavily on the sensitivity of existing turbo equalization methods to 2D channel parameter mismatch

Dates et versions

hal-01347980 , version 1 (22-07-2016)

Identifiants

Citer

Frederic Lehmann. Joint binary image deconvolution and blur identification in the context of two-dimensional storage channels. Signal Processing, 2011, 91 (10), pp.2426 - 2431. ⟨10.1016/j.sigpro.2011.04.027⟩. ⟨hal-01347980⟩
24 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More