Independent Comoponent Analysis Method And Its Applications To Infrared Image Processing

Independent Component Analysis(ICA) is an efficient approach to blind signal separation, now many applications of image processing base on ICA,such as image edge extraction,image denoise,identification on people's face,image separation,medical image dealing and so on.In recent years, infrared images are widely applied to many areas. However, much noise and blurred edge is a serious problem to the infrared images because of the inherent character of infrared detectors.In order to reduce these problems,many boffin researcher make abundant works,got a lot of success.The paper discuss the principle of ICA,it simply descripts the development,application and status about ICA,and it mainly focuses on ICA application of image,The method makes ICA together with wavelet and fractional derivative on infrared image denoising and edge extract.The main works: According to MSD-ICA' principle, we can get the corresponding sub-image by decomposition of wavelet transform. Then,using ICA to de-noise the infrared image;According to fractional dericative principle, first,we can get the image enhanced by fractional derivative approach ,then use ICA to extract the reinforced image.The experimental result shows that the ICA has the great effect on dealing of infrared image ,it can not only de-noising ,but also keep the character of intrinsic image well.This is pay to infrared image's process.also shows that the fractional derivative approach can enhance the smooth area of image and the ICA has the great effect on extracting the edge of infrared image even if there is any noise exist.