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.
Document Type: Research Article
Affiliations: Key Laboratory of Water Cycle and Related Land Surface Processes, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Publication date: June 1, 2008