Title

Two-Dimensional Optimum Block Adaptive Filtering Algorithms For Image Restoration And Enhancement

Abstract

In this paper, two new fast gradient algorithms employing convergence factors which are optimized in the least-squares sense, which perform two-dimensional block adaptive filtering are presented. These two algorithms are termed as the two-dimensional optimum block algorithm with individual adaptation of parameters (TDOBAI) and the two-dimensional optimum block adaptive algorithm (TDOBA). The convergence properties of the TDOBAI and the TDOBA algorithm are investigated and compared with the two-dimensional block least-mean-square (TDBLMS) algorithm which uses a convergence factor that is constant for each 2-D coefficient at each block iteration, using computer simulations. It is also shown that for the TDOBAI and TDOBA algorithms, the convergence, speed and accuracy of adaptation are greatly improved at the expense of a modest increase in computational complexity, as compared to the TDBLMS algorithm. The effectiveness of the algorithms is demonstrated in 2-D system modeling, restoration (2-D additive noise cancellation) and enhancement of artificially degraded images.

Publication Date

1-1-1993

Publication Title

Proceedings - IEEE International Symposium on Circuits and Systems

Volume

1

Number of Pages

419-422

Document Type

Article; Proceedings Paper

Identifier

scopus

Personal Identifier

scopus

Socpus ID

0027308588 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0027308588

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