Using Gis Data to Identify Linear Observation Model on Remote Sensing Images in Case of Spatial Mismatch of Input Image and Vector Map

Abstract

Abstract. This paper presents an experimental research of identification method proposed by the authors in their previous works. The method was developed to identify a linear observation model in remote sensing images. It uses the relation between energy spectra of input and output images, and it is called energy spectrum method. The latest modification of the method applies vector map data from geoinforation system to construct an image with energy spectrum similar to energy spectrum of unknown undistorted image. Vector map and input image had been supposed to be exactly spatially coherent. In this paper the algorithm's quality is investigated in case of inexact spatial matching of input image and vector map. Accuracy of input image georeference and accuracy of vector map borders are considered as major spatial mismatch factors. Experimental evaluation of the these factors influence on quality of impulse response restoration is provided. IntroductionThe common way to describe the process of image acquisition in remote sensing systems is a linear observation model [1]. For different applications, for example, for image correction, it is important to estimate the parameters of the model using only observed image. State of the art methods of system's impulse response identification [2-4] work mainly with one dimensional signals or have high computational complexity, that significantly impedes their use in case of remote sensing images.