TY - JFULL AU - V. K. Ananthashayana and Jyothirmayi M. PY - 2009/9/ TI - Blind Source Separation Using Modified Gaussian FastICA T2 - International Journal of Computer and Information Engineering SP - 2025 EP - 2029 VL - 3 SN - 1307-6892 UR - https://publications.waset.org/pdf/12887 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 32, 2009 N2 - This paper addresses the problem of source separation in images. We propose a FastICA algorithm employing a modified Gaussian contrast function for the Blind Source Separation. Experimental result shows that the proposed Modified Gaussian FastICA is effectively used for Blind Source Separation to obtain better quality images. In this paper, a comparative study has been made with other popular existing algorithms. The peak signal to noise ratio (PSNR) and improved signal to noise ratio (ISNR) are used as metrics for evaluating the quality of images. The ICA metric Amari error is also used to measure the quality of separation. ER -