Abstract

Abstract. The detection of orthoimage mosaicking seamlines by means of wavelet transform was examined. Radiometric alignment was omitted, giving priority to the issue of seamlines which bypass locations where there is a parallax between orthoimages. The importance of this issue is particularly relevant for images with very high resolution. In order to create a barrier image between orthoimages, the redundant wavelet transform variant known as MODWT-MRA was used. While more computationally complex than the frequently used DWT, it enables very good multiresolution edge detection. An IT prototype was developed on the basis of the described concept, and several cases of seamline detection were tested on the basis of data with a resolution of 10 cm to 1 m. The correct seamline location was obtained for each test case. This result opens the door to future expansion of the radiometric alignment method, which is also based on wavelets.

Highlights

  • Mosaicked orthoimages are probably the most popular type of map

  • The goal of mosaicking line detection is to exclude all places where there is a difference between orthoimage edges, textures, and radiometry

  • Continuous wavelet transform (CWT) involves combining a signal with a function characterised by a limited life and an average value of zero

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Summary

INTRODUCTION

Mosaicked orthoimages are probably the most popular type of map. This is due to their low development costs compared with vector maps, as well as to very well-developed methods of compression and transmission of large raster files. Wavelets are used widely in research, for example, to remove noise in radar images, to perform fusion (merging) of images with different spatial resolutions, to describe structural features for image classification, and to perform image matching (Nuñez et al, 1999; Ranchin, Wald, 2000; Shi et al, 2005; Heygster et al, 2010; Tello et al, 2011). It has not been used for the detection of mosaicking lines.

RELATED WORK
WAVELET TRANSFORM
Implementation of DWT according to the Mallat algorithm
Maximal Overlap DWT and Multiresolution Analysis
Detection of Image Edge
CONCEPT OF USING WAVELETS TO DETECT SEAMLINES
SCOPE OF EXPERIMENTAL WORK
RESULTS AND CONCLUSIONS
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