Abstract
Abstract. The pan-sharpening is a widely used operation in remote sensing image processing, this operation aims at combining an observable high spatial resolution panchromatic image with a multispectral one, to generate an unobservable image with the high spatial resolution of the former and a high spectral resolution of the latter. Generally, papers dealing with this problem omit the geometric part and suppose that these images are perfectly aligned, which is not necessarily the case for the raw imagery, where even the different bands in the multispectral imagery are misaligned. In this paper, new method for multispectral and panchromatic image registration is proposed to deal with the misalignment problem that reduces the pansharpening quality. This method called Dense Vector Matching (DVM) is based on the matching of a whole line-vector or column-vector from a reference band with the corresponding vector in a target band. DVM is applied on real data and has given acceptable results, where the QNR index of the pan-sharpening is better for images after band registration, also the registration error is reduced to sub-pixel using the proposed approach.
Highlights
Pan-sharpening, land-cover classification, change detection...etc are applications that involve the use of multispectral remote sensing images, which require that the same image position, in all bands, corresponds to the same pixel on the ground
This paper deals with the correction of the intra and inter band registration error in the PAN and the MS imagery, this approach is designed for Alsat-2 the Algerian high spatial resolution satellite in the aim of enhancing the pansharpening
This approach uses a newly proposed method for band to band registration called Dense Vector Matching (DVM), this method is based on a non-centered cross correlation technique, wherein each line-vector and each column-vector of a given target band is aligned with the corresponding vectors of the chosen reference band
Summary
Pan-sharpening, land-cover classification, change detection...etc are applications that involve the use of multispectral remote sensing images, which require that the same image position (row, column), in all bands, corresponds to the same pixel on the ground. The second category includes “image-based registration” methods that does not require the knowledge of satellite position and orientation (Radhadevi et al 2009) In this category, some pixels on target bands are matched with corresponding pixels in a reference band to measure the registration errors (Fang et al 2012; Ma and Zhang 2009; Pan et al 2011; Lehner and Kornus 1999). The main advantage of this process is to enhance the spatial/spectral resolutions without disturbing the raw image geometry that remains the same as the reference band This allow us to use the obtained “geometrically. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2, 2018 ISPRS TC II Mid-term Symposium “Towards Photogrammetry 2020”, 4–7 June 2018, Riva del Garda, Italy raw pan-sharpened” image in a photogrammetric orthorectification process without any modification in the image metadata
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