Feature space and metric measures for fusing multisensor images

Abstract

A multivalued wavelet transform (MWT) is proposed to fuse multisensor images in feature space. First, feature space is constructed using image‐derived features, and then the MWT is introduced. The multisensor images are then fused in the MWT domain using a voting and electing fuser based on the cross‐feature scale guideline and the posterior probability of the MWT coefficient. The performance of the MWT is estimated using metric measures regarding various aspects of image quality. A fusion experiment using Thematic Mapper (TM) multispectral and SPOT panchromatic images of south China demonstrates that MWT outperforms smoothing filter‐based intensity modulation (SFM) in terms of the fidelity to spectral properties and the injection of salient information. The experimental results confirm that the MWT is a superior fusion method for enhancing spatial quality of multispectral images with their spectral properties reliably preserved.