作者: Shaohui Chen , Renhua Zhang , Hongbo Su , Jing Tian , Jun Xia
DOI: 10.5589/M08-068
关键词: Cognitive neuroscience of visual object recognition 、 Image resolution 、 Support vector machine 、 Moderate-resolution imaging spectroradiometer 、 Image fusion 、 Hilbert–Huang transform 、 Remote sensing 、 Thematic Mapper 、 Geography 、 Spectral signature
摘要: In existing image fusion methods, there is little work concerning the of Moderate Resolution Imaging Spectroradiometer (MODIS) images with Landsat Thematic Mapper (TM) images. most cases, object reflectance property and sensor spectral response are not considered, which produces some undesirable effects such as decreased resolution over injection slightly modified signatures in features. Starting from a simplified land surface reflection model, we deduce general method that takes both aspects into account for injecting features TM MODIS images, trying to preserve latter improve spatial former. This further improved using empirical mode decomposition (EMD) by considering difference between detail radiation absent appearing image. experiment, visual inspection Wald's protocol used assess qualities fused qualitatively quantitatively, respectively. Compared many state-of-the-art proposed closer corresponding virtual would observe if it worked at Extensive assessment results demonstrate encouraging increasing details its properties reliably preserved. The recommended useful tool significantly different resolutions.