In this work, a multi-resolution procedure based on a generalized Laplacian pyramid (GLP), with p : q (i.e. rational) scale factor, is proposed to merge image data of any resolution and represent them at any scale. The GLP-based data fusion is shown to be slightly superior to those of a similar scheme based on the discrete wavelet transform, (WT) according to a set of parameters established in the literature. Not only fused images look sharper than their original versions, but also textured regions are enhanced without losing their spectral signatures. The pyramid-generating filters can be easily designed for data of any resolutions, differently from the WT, whose filter-bank design is non-trivial when the ratio between the scales of the images to be merged is not a power of two. Eventually, remotely sensed images from LandSat TM and from Panchromatic SPOT are fused together. The resulting bands capture multi-spectral features with enhanced contrast and texture, and an increased spatial resolution, thereby expediting automatic analyses for contextual interpretation of the environment.

Pyramid-based multisensor image data fusion

L Alparone;S Baronti;
1997

Abstract

In this work, a multi-resolution procedure based on a generalized Laplacian pyramid (GLP), with p : q (i.e. rational) scale factor, is proposed to merge image data of any resolution and represent them at any scale. The GLP-based data fusion is shown to be slightly superior to those of a similar scheme based on the discrete wavelet transform, (WT) according to a set of parameters established in the literature. Not only fused images look sharper than their original versions, but also textured regions are enhanced without losing their spectral signatures. The pyramid-generating filters can be easily designed for data of any resolutions, differently from the WT, whose filter-bank design is non-trivial when the ratio between the scales of the images to be merged is not a power of two. Eventually, remotely sensed images from LandSat TM and from Panchromatic SPOT are fused together. The resulting bands capture multi-spectral features with enhanced contrast and texture, and an increased spatial resolution, thereby expediting automatic analyses for contextual interpretation of the environment.
1997
Istituto di Fisica Applicata - IFAC
0-8194-2591-5
Multi-sensor image fusion
multi-spectral images
wavelet transform
generalized Laplacian pyramid
rational scale factor
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/230379
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