Multispectral image data fusion using POCS and super-resolution
The problem of image data fusion coming from different sensors imaging the same object is to try to obtain a result that integrates the best characteristics of each one of those sensors. In this work, we want to combine the characteristics of multispectral (better spectral definition) and panchromatic (better space definition) images, using the bands from the satellites Landsat-7 (panchromatic) and CBERS-1China-Brazil Earth Resources Satellite (four multispectral bands). The process proposes solutions using projection onto convex sets (POCS) techniques divided in two steps: (a) interpolated image processing, regularizing the block artifacts and using super-resolution techniques based on POCS and (b) synthesis, obtained by sequential and parallel projections or by the least squares method.
image data fusion super-resolution projections onto convex sets remote sensing images synthesis image interpolation