Efficient shadow detection by using PSO segmentation and region-based boundary detection technique

The presence of shadows in satellite images is inevitable, and hence, shadow detection and removal has become very essential. In this paper, a shadow detection algorithm based on PSO has been used to identify shadows in very high-resolution satellite images. The image is first preprocessed using a b...

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Bibliographic Details
Published inThe Journal of supercomputing Vol. 75; no. 7; pp. 3522 - 3533
Main Authors Usha Nandini, D., Leni, Ezil Sam
Format Journal Article
LanguageEnglish
Published New York Springer US 01.07.2019
Springer Nature B.V
Subjects
Algorithms
Compilers
Computer Science
Edge detection
Image detection
Image resolution
Image segmentation
Interpreters
Object recognition
Processor Architectures
Programming Languages
Satellite imagery
Shadows
Boundary detection
Shadow
Shadow detection
Bilateral filtering
Particle swarm optimization
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ISSN0920-8542
1573-0484
DOI10.1007/s11227-018-2292-y

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Summary:The presence of shadows in satellite images is inevitable, and hence, shadow detection and removal has become very essential. In this paper, a shadow detection algorithm based on PSO has been used to identify shadows in very high-resolution satellite images. The image is first preprocessed using a bilateral filter to eliminate the noise followed by which PSO-based shadow segmentation is used to segment the shadow regions. Canny edge detection is done to identify the edges of the objects in the image. The results of the edge detection and segmentation are combined using a logical operator to generate the final shadow segmented image with well-defined boundaries. The accuracy is validated using precision and recall parameters.
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-018-2292-y