A simplified ICA based denoising method

Author

Zhang, Qingfu ; Yin, Hujun ; Allinson, Nigel M.

Author_Institution

Dept. of Electr. Eng. & Electron., Univ. of Manchester Inst. of Sci. & Technol., UK

Volume

5

fYear

2000

fDate

2000

Firstpage

479

Abstract

Hyvarinen et al. (2000) have developed an ICA based method for image denoising. The major advantage of their method is that the transformation matrix can by adjusted to suit the available data. However, in their method, the transformation matrix and shrinkage parameters need to be learned from noise-free data. In this paper, we propose a simplified shrinkage scheme, which has only one heuristic control parameter. Experimental results show that the ICA based method with this new shrinkage scheme achieves comparable performance to that of Hyvarinen et al

Keywords

heuristic programming; image processing; matrix algebra; neural nets; principal component analysis; heuristic control parameter; image denoising; neural net; shrinkage parameters; simplified ICA based denoising method; transformation matrix; Gaussian noise; Image denoising; Independent component analysis; Maximum likelihood estimation; Noise reduction; Parameter estimation; Signal denoising; Training data; Wavelet transforms; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2000. IJCNN 2000, Proceedings of the IEEE-INNS-ENNS International Joint Conference on

Conference_Location

Como

ISSN

1098-7576

Print_ISBN

0-7695-0619-4

Type

conf

DOI

10.1109/IJCNN.2000.861515

Filename

861515