Cloud covering denoising through image fusion

This paper presents a solution to the cloud removal problem, based in a recently developed image fusion methodology consisting in applying a 1-D pseudo-Wigner distribution (PWD) transformation to the source images and on the use of a pixel-wise cloud model. Both features could also be interpreted as a denoising method centered in a pixel-level measure. Such procedure is able to process sequences of multi-temporal registered images affected with spatial-variant noise. The goal consists in providing a 2-D clean image, after removing the spatial-variant noise disturbing the set of multi-temporal registered source images. This is achieved by taking as reference a statistically parameterized model of a cloud prototype. Using this model, a pixel-wise measure of the noise degree of the source images can be calculated through their PWDs. This denoising procedure enables to choose the noise-free pixels from the set of given source images. The applicability of the method to the cloud removal p...

• Type: Journal
• Year: 2007
• Where: IVC
• Authors: Salvador Gabarda, Gabriel Cristóbal
• Keywords: Cloud Removal, Images, IVC 2007, Source Images