Electrica, vol.3, no.24, pp.812-817, 2024 (ESCI)
Synthetic aperture radar (SAR) is an important and efficient imaging
technology. This system provides robust information for various
applications such as ship detection, climate change, and agricultural
land modeling. Ship detection and classification problem is an important
object detection problem that involves difficulties. There are
deep-learning-based studies to solve this problem. However, mathematical
and statistical methods should be developed for ship classification
applications. In this paper, gray-level co-occurrence matrix-based
method is proposed. The gradient of the input SAR image was calculated
using Gaussian derivative filters. The gradient magnitude was calculated
with horizontal and vertical gradient information. Gray-level
co-occurrence matrix was obtained using gradient magnitude. The
meaningful features of the images were calculated by performing 4
different statistical calculations. Results on our SAR database reveal
the proposed model's superior classification performance.