IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Online ISSN : 1745-1337
Print ISSN : 0916-8508
Regular Section
Filtering in Generalized Signal-Dependent Noise Model Using Covariance Information
Seiichi NAKAMORIMaría J. GARCÍA-LIGEROAurora HERMOSO-CARAZOJosefa LINARES-PÉREZ
著者情報
ジャーナル 認証あり

2008 年 E91.A 巻 3 号 p. 809-817

詳細
抄録
In this paper, we propose a recursive filtering algorithm to restore monochromatic images which are corrupted by general dependent additive noise. It is assumed that the equation which describes the image field is not available and a filtering algorithm is obtained using the information provided by the covariance functions of the signal, noise that affects the measurement equation, and the fourth-order moments of the signal. The proposed algorithm is obtained by an innovation approach which provides a simple derivation of the least mean-squared error linear estimators. The estimation of the grey level in each spatial coordinate is made taking into account the information provided by the grey levels located on the row of the pixel to be estimated. The proposed filtering algorithm is applied to restore images which are affected by general signal-dependent additive noise.
著者関連情報
© 2008 The Institute of Electronics, Information and Communication Engineers
前の記事 次の記事
feedback
Top