Fusion of 18m MOMS-2P and 30m Landsat TM multispectral data by the generalized Laplacian pyramid

Goal of this work is to present a general and formal solution to the problem of synergetic integration of multi-sensor image data, which may be collected with practically whatsoever spectral and ground resolution, although scale ratios larger than, say, 10, may be questionable in certain applicative contexts. The proposed data fusion methodology is applied to a specific example concerning observations from two different multi-spectral satellite sensors: Landsat TM (30 m resolution) and MOMS-2P (18 m ). The fusion procedure relies on the generalized Laplacian pyramid (GLP), which is a non-octave band-pass analysis structure unconstrained from the ground scales of the imaged data. The advantage is that the base-band extracted from the finer image exactly matches both in displaying scale and in resolution, i.e. content of spatial frequencies, the coarser image. For any rational scale ratio, a unique low-pass filter is needed. The filter design, however, is easy and noncritical for performances. The GLP scheme is superior in enhancing spatial features while retaining multi-spectral signatures, according to both objective and subjective quality criteria. The experiment reported highlights the assets of the pyramid approach: 5:3 fusion is designed for spectral enhancement of MOMS-2P (three 18 m bands) through Landsat TM (six 30 m bands). Since the three available multi-spectral bands of MOMS-2P overlap with Bands 2, 3, and 4 of TM, the test consists of synthesizing the three missing MOMS-2P bands -one in the blue and two in the infrared wave-lengths- from the TM data, in order to obtain 18 m R-G-B true colour and three 18 m bands in near-medium infrared.