ABSTRACT

Information provided from a single spectral band of a satellite image, may not be sufficient in most cases for classification, recognition and change detection applications. Therefore, bands with different spectral and spatial characteristics are combined to obtain a single fused image that contains complementary information. This study introduces a novel hybrid fusion method for remotely sensed infrared and visible images based on backtracking search algorithm (BSA) and Shearlet transform. Shearlet is an efficient processing method to transform spatial information and BSA is a powerful metaheuristic optimization method. Combining these techniques offers an efficient way to fuse low-resolution infrared and high-resolution panchromatic bands of satellite images. Extensive experiments proved that proposed method outperforms well-known multi-scale transforms based fusion methods in terms of both numerical and visual evaluations.

摘要

在大多数情况下，从卫星图像的单个光谱带提供的信息可能不足以进行分类，识别和变化检测应用。因此，具有不同光谱和空间特征的波段被组合以获得包含互补信息的单个融合图像。本研究介绍了一种基于回溯搜索算法（BSA）和Shearlet变换的遥感和可见光图像混合融合新方法。Shearlet是转换空间信息的有效处理方法，而BSA是强大的元启发式优化方法。结合这些技术可提供一种有效的方法来融合卫星图像的低分辨率红外和高分辨率全色波段。