Abstract
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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