HSI Image Restortion using Low Rank Matrix Recovery

Abstract

Restoration is process of undoing or recovering an image from degraded state. The image restoration techniques are used to make the corrupted image as similar as that of the original image. Hyper spectral image are often corrupted by a mixture of various kinds of noise in the acquisition process, which can include Gaussian noise, impulse noise, deadlines, stripes, and so on. Various restoration methods are used. A new HSI restoration method based on low-rank matrix recovery (LRMR) is introduced, which can simultaneously remove the Gaussian noise, impulse noise, deadlines, and stripes but there is no spatial constraint applied on neighbouring pixels that causes large areas of missing pixels .To handle the problem of missing pixels non-reference regularization algorithm is used .