Image denoising based on blind source separation.
Wang Run-shen, Atr Lab · Computer Engineering and Applications Journal · 2007
Removing noise from the original signal is still an important and challenging problem for researchers.In spite of the sophistication of the recently proposed methods,most algorithms have not yet attained a desirable level of applicability.All show an outstanding performance when the image model corresponds to the algorithm assumptions,but fails in general and creates artifacts or removes image fine structures.In this paper the image and the noise are considered as two independent sources which mixed together.If we can separate the two sources,the aim to denoise is achieved.Blind Source Separation(BSS) techniques such as Independent Component Analysis(ICA) lend themselves well to analyse such problems.A dummy observation will be estimated from the corrupted image,and an image denoising algorithm based on BSS is presented.Demonstration indicates that the proposed method gives better result compared to conventional method.