Implementación y generación de un algoritmo (TWD) no decimado para la fusión de imágenes satelitales Ikonos

Abstract

Satellite image fusion has been widely used in different areas of digital processing such as: pattern recognition, increased spatial or spectral resolution, and multitemporal studies (Dong, Zhuang, Huang, & Fu, 2009). Said fusion is carried out with various methods, which are set out below: principal component analysis (PCA), Brovey transform (BT) (Rumora et al., 2020) or Wavelet transforms. In the latter, the Mallat or À trous decomposition algorithms can be used in search of the coefficients that have the highest spatial resolution. Several studies in this regard have been carried out with the Mallat decomposition algorithm proposed in 1989 (Félix et al., 2014), (Abdipour & Nooshyar, 2016) and (Singh et al., 2017). However, authors such as Tirupal et al., 2016 and Gambhir & Manchanda, 2015, have demonstrated the efficiency of the use of the À trous' algorithm (Dutilleux, 1990) due to its mathematical properties and its attempt to conserve spectral and spatial richness. From this perspective, an implementation and evaluation of the À trous' algorithm was considered essential with a new approach, based on the spatial filter, on different images from remote sensors, in order to obtain less spectral degradation and preserve a greater spatial richness in the images.