Abstract
The present paper proposes a novel approach for edge detection in satellite images based on cellular neural networks. CNN based edge detector in used conjunction with image enhancement and noise removal techniques, in order to deliver accurate edge detection results, compared with state of the art approaches. Thus, considering the obtained results, a comparison with optimal Canny edge detector is performed. The proposed image processing chain deliver more details regarding edges than canny edge detector. The proposed method aims to preserve salient information, due to its importance in all satellite image processing applications.
Highlights
The use of satellite imagery in everyday life is no more a novelty
Edge detection is an image processing task used in various types of image processing applications
In case of satellite image processing, edge detection it is of high importance due to the fact it detects different areas of interest for different applications
Summary
The use of satellite imagery in everyday life is no more a novelty. The first satellite for acquiring land areas imaging was placed in orbit in 1972 (Landsats) )1(. The rapid advances and accessibility of computer technology brought satellite images in millions of homes, cars, schools, and offices. Satellite imagery provides accurate information of observing and quantifying the surface of the earth. The main benefit is the increased knowledge about our environment
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