SAR Image Segmentation and Target Detection Based on Mathematical Morphology

Mathematical morphology provides a method of image processing based on the concept of shape in set theory rather than standard mathematical modeling and analysis, especially when dealing with image processing problems including edge detection, image filtering, feature extraction, and image segmentation. The advantages of using the mathematical morphology method are evident. Using mathematical morphology methods for image segmentation and target detection to aim at specified targets in SAR pictures such as buildings,high-voltage towers, and so on, based on mathematical morphology theory research. To begin, pre-filter the original SAR image to reduce some of the image's noise. The image is then binarized utilizing mathematical morphological processes such as erosion, dilation, opening, and closing. Various forms can be used depending on the target's shape. The image is segmented using morphological operators. Finally,the segmentation findings are used to perform target extraction and detection, with good results for buildings, high-voltage towers, and other objects in the SAR image.