Performance of Phase Congruency and Linear Feature Extraction for Satellite Images Using Smoothing Algorithm
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2013, Vol 12, Issue 1
Abstract
In computer vision all of the existing researches are interested in synthetic images features extraction. These images contain many types of features. Moreover, the satellite images are one most complex real image. Accordingly, many researches are developed in this way. The satellite images present a great variety of features due to the trouble what returns their treatment is little delicate. The automated extraction of linear features from remotely sensed imagery has been the subject of extensive research over several decades. Recent studies show promise for extraction of feature information for applications such as updating geographic information systems (GIS). Research has been stimulated by the increase in available imagery in recent years following the launch of several airborne and satellite sensors. In this paper, we introduce a new application of linear and phase congruency model for features extraction in satellite images. The aim of this paper is to exploit the advantages and the limitations of this model applied in satellite images features extraction. On the other hand, Adaptive minutia preserving smoothing algorithm used to improve the features extraction procedure. The paper also describes methods used for feature extraction and considers quantitative and qualitative accuracy assessment of these procedures
Authors and Affiliations
J. Krishna Chaithanya
Keywords
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