Two-dimensional joint process lattice for adaptive restoration of images

Author

Youlal, Hussein ; Janati-I, Malika ; Najim, Mohamed

Author_Institution

Fac. des Sci., Rabat Univ., Morocco

Volume

1

Issue

3

fYear

1992

fDate

7/1/1992 12:00:00 AM

Firstpage

366

Lastpage

378

Abstract

The two dimensional (2D) joint process lattice (TDJPL) and its implementations for image restoration applications are examined. A 2D adaptive lattice algorithm (TDAL) is first developed. Convergence properties of the algorithm are covered for the 2D adaptive lattice least mean squares (TDAL-LMS) case. The complexity of the normalized algorithm is slightly more than that of the TDAL-LMS, but it is a faster-converging algorithm. Implementations of the proposed TDJPL estimator as a 2D adaptive lattice noise canceler and as a 2D adaptive lattice line enhancer are then considered. The performance of both schemes is evaluated using artificially degraded image data at different signal-to-noise ratios (SNRs). The results show that substantial noise reduction has been achieved, and the high improvement in the mean square error, even at very low input SNR, is ensured. The results obtained consistently demonstrate the efficacy of the proposed TDJPL implementations, and illustrate the success in its use for adaptive restoration of images

Keywords

convergence; interference suppression; noise; picture processing; 2D adaptive lattice algorithm; 2D joint process lattice; artificially degraded image data; convergence; image restoration; line enhancer; low input SNR; mean square error; noise canceler; normalized algorithm; signal-to-noise ratios; Adaptive algorithm; Change detection algorithms; Convergence; Image restoration; Image sequences; Lattices; Least squares approximation; Signal processing algorithms; Signal to noise ratio; Two dimensional displays;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/83.148609

Filename

148609