Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Low-complexity Turbo-equalization for diversity channels
Signal Processing
A unified method for optimizing linear image restoration filters
Signal Processing - Image and Video Coding beyond Standards
Restoration of scanned photographic images
Signal Processing
Improved turbo equalization based on soft ISI cancellation
Signal Processing
IBM Journal of Research and Development
Optimal decoding of linear codes for minimizing symbol error rate (Corresp.)
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
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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.