In this paper, a new multispectral image wavelet representation is introduced, based on multiscale fundamental forms. This representation describes gradient information of multispectral images in a multiresolution framework. The representation is in particular extremely suited for the fusion and merging of multispectral images. For fusion as well as for merging, a strategy is described. Experim...

A pixel level data fusion approach based on correspondence analysis (CA) is introduced for high spatial and spectral resolution satellite data. Principal component analysis (PCA) is a well-known multivariate data analysis and fusion technique in the remote sensing community. Related to PCA but a more recent multivariate technique, correspondence analysis, is applied to fuse panchromatic data wi...

Image fusion is the process of merging two or more images obtained from the same sensor at different times or from two or more sensors at the same instant. The objective is to obtain more information from the fused image than from the individual images. In satellite images, the lower spatial resolution multispectral images are fused with higher spatial resolution panchromatic images. The fusion...

In remote sensing applications, lower spatial resolution multispectral images are fused with higher spatial resolution panchromatic ones. The objective of this fusion process is to enhance the spatial resolution of the multispectral images to make important features more apparent for human or machine perception. This enhancement is performed by injecting the high frequency component of the panc...

Pixel-level image fusion combines complementary image data, most commonly low spectral-high spatial resolution data with high spectral-low spatial resolution optical data. The presented study aims at refining and improving the High-Pass Filter Additive (HPFA) fusion method towards a tunable and versatile, yet standardized image fusion tool. HPFA is an image fusion method in the spatial domain, ...

In this paper, we will investigate techniques for the combination of image fusion and segment based image analysis. We describe a color preserving iconic fusion with subsequent segmentation and classification, a ‘cookie cutter’ approach for the integration of high resolution RGB and low resolution hyperspectral image data and a decision based fusion technique, that combine high resolution panch...

Image data fusion is the process of setting together information gathered by different heterogeneous sensors, mounted on different platforms. This paper presents an effective multi-resolution image data fusion methodology, which is based on utilizing the Principal Component Analysis “PCA” and Histogram Specification “HS” techniques. The first principal component “PCA1” involves much of the vari...

The spatial resolution of hyperspectral image is often low due to the limitation of the imaging spectrometer. Fusing the original hyperspectral image with high-spatialresolution panchromatic image is an effective approach to enhance the resolution of hyperspectral image. However, it is hard to preserve the spectral information at the same time of enhancing the resolution by the traditional fusi...

Over the last years, image fusion techniques have gained a renewed interest within the remote sensing community. The reason for this is that in most cases the new generation of remote sensors with very high spatial resolution records image datasets in two separate modes: the highest spatial resolution is obtained for panchromatic images whereas multispectral information is associated with lower...