Digital Image Processing

Mohammed Y. Abbass ¹, Safey A. Abdelwahab ¹, Salah M. Diab ², Bassiony M. Salam ², El-Sayed M. El-Rabaie ², Fathi E. Abd El-Samie ², Said S. Haggag ³

Affiliations
1 Engineering Department, Nuclear Research Center, Atomic Energy Authority, EG
2 Department of Electronics and Electrical Communications, Menoufia University, Menouf, EG
3 Nuclear Research Center, Atomic Energy Authority, EG

Abstract

This paper deals with the problem of blind separation of digital images from mixtures. A method to solve this problem is blind source separation (BSS) using independent component analysis (ICA). It proposes a wavelet based ICA method using Kurtosis for blind image source separation. In this method, the observations are transformed into an adequate representation using wavelet packets decomposition and Kurtosis criterion. The simulation results of performance measures show a considerable improvement when compared to FastICA. The Peak Signal-to-Noise Ratio (PSNR), Signal-to-Noise Ratio (SNR), Root Mean Square Error (RMSE) and and Segmental Signal-to-Noise Ratio (SNRseg) are used to evaluate the quality of the separated images.

Keywords

Blind Source Separation (BSS), ICA, Kurtosis.

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