Introducing object reflectance property and sensor spectral response into empirical mode decomposition based MODIS and TM image fusion

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 recognitionImage resolutionSupport vector machineModerate-resolution imaging spectroradiometerImage fusionHilbert–Huang transformRemote sensingThematic MapperGeographySpectral 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.

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