Abstract

The aim of the following study was to develop a procedure which guarantees the data fusion of thermal and visual images. The first stage of the proposed algorithm consisted of images acquisition which guaranteed that the same parts of images represented the same parts of the observed terrain. The second stage depended on previous information about the searched object features. Two different situations were considered herein. In the case when we had the searched object’s feature vector for both representations of a searched object, we could conduct the pattern recognition for each image. It was conducted separately for visual and thermal images. In this way, we obtained the important parts of the images which should be represented in a fused image. The other case examined in the paper, considered the situation in which we did not have the formalised information about the object. In this case, it was necessary to analyse whole images in order to define the potential parts of the images where the object could be found. This analysis should be helpful for an operator to indicate the parts of the images where there are some artefacts which can be the elements of the searched object. Therefore, in this case, the second stage of the algorithm consisted in calculating the local features of the images. These features constituted grey scale gradient computed for the pixels inside the aperture. This study presented the examples of the fused images obtained by means of the developed method.

Highlights

  • The fusion of various nature images is valuable when it is used for a support of terrain observations or surveying the objects by the video terminal operator

  • We may use the algorithms of pattern recognition to emphasise the parts of the images which contain the important objects when we know some features of these objects

  • We have developed two procedures which allow to conduct the data fusion of thermal and visual images

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Summary

Introduction

The fusion of various nature images is valuable when it is used for a support of terrain observations or surveying the objects by the video terminal operator. Otherwise we can use the methods of an edge detection or gradient computation assuming that greater homogenous areas do not contain any important objects. Even in this case, it is necessary to define what we mean by a greater or smaller area. The security area can be supported by the images fusion The examples of such systems are presented in [7,8] for detection of unattended packages and for helping drivers with driving at night or in bad weather conditions [7]. We will consider the problem of the visual and thermal images fusion. We will use information about observed objects, and secondly, we will analyse the images without any previous information

The algorithm for visual and infrared images fusion
Examples
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